research proposal for engineering design

Thesis Proposal

Note: This article is partially based on the 2017-2018 MechE Graduate Student Guide (PDF) . Please check the latest guide for the most-up to date formatting requirements.

Criteria for Success

A strong thesis proposal…

• Motivates your project and introduces your audience to the state-of-the-art for the problem you’re working on.
• Explains the limitations in the current methods through literature review and/or original analysis. This should also explain why the limitations matter and why they’re the right ones to focus on.
• Clearly explains your technical approach to make specific improvements to some part of the field.
• Uses original analysis and literature to support the feasibility of the approach.
• Describes what is original about your work.
• Provides a practical outline for completing this research : a degree timeline laying out quantifiable hypotheses, experimental/numerical/theoretical techniques, and metrics for evaluation .

Structure Diagram

Meche-specific structure requirements.

Your thesis proposal should be limited to 6 pages including figures and references.

In addition, you need a cover page that (only) includes:

• tentative title of the thesis
• brief abstract
• committee chair and/or advisor should be indicated
• include their official titles, departmental affiliations, and email addresses

The purpose of your thesis proposal is to introduce your research plan to your thesis committee. You want the committee members to come away understanding what your research will accomplish, why it is needed ( motivation ), how you will do it ( feasibility & approach ), and most importantly, why it is worthy of a PhD ( significance ).

You intend to solve a real and important problem, and you are willing to dedicate years of your life to it, so use your proposal to get the committee excited about your research!

Analyze your audience

Unlike many of the papers and presentations you will write during graduate school, only a select few people will read your thesis proposal. This group will always include your PhD committee and your research advisor, and may include other interested MechE faculty or scientists and engineers at your funding source.

Therefore, you will typically have a good understanding of your audience before it is written. This can allow you to tailor your message to the technical level of your specific audience. If you aren’t sure what your audience could reasonably be expected to know, be conservative! Regardless, your audience is always looking to answer the questions: “ what is this research, how will you perform it, and why does it matter?”

While the small audience may make you less interested in committing time to your proposal, the exercise of motivating and justifying your work plan will be critical to your PhD.

Follow the standard structure for research proposals

While some variation is acceptable, don’t stray too far from the following structure. See also the Structure Diagram above.

• Introduction . Provide only the necessary information to motivate your research, and show how it fits into the broader field. What is the problem you are trying to solve? By the end of the introduction, your audience should understand the basics of what you will do and why you will do it.
• Background/Methodology . Describe the current state of the art and related research fields in sufficient technical detail. The goal is provide just enough detail to give the reader a sound understanding of the limitations and the need for new work. Do not go into detail that does not directly help in understanding your You are not trying to make your reader understand everything about the topic or demonstrate how much you know.
• Objectives . Although not strictly necessary, this section lets you summarize concrete goals of your work, and can help to serve as a checklist for yourself as you move through the process. This is best for projects that tackle many interrelated problems. Think of this as a list of concrete (quantifiable) goals that you want to accomplish.
• Proposed Work. Explain how your work will solve the problems that you have identified. How will you address the objectives above? Provide just enough technical specificity to leave the reader with a firm grasp of what you will do.
• Provide a set of time-structured goals and deliverables. While this is not strictly necessary, your committee will want a timeline when you meet with them, so it can help to start planning now. You want to graduate, so make sure that you have a plan to do so!
• This is a standard section listing references in an appropriate format (MLA, APA, etc.)

Consider the logical sequence of your sections. After the introduction, your audience should be intrigued by a key problem, and intrigued that you know how to solve it. Through the background, they learn that this problem is more difficult than they originally realized. Finally, in the proposed work they learn that your proposal addresses the additional complexity introduced in the background, and they have confidence that you can actually solve the problem.

Summarize the current research field

You need to have a strong grasp of the broader research community. How can you contribute, if you don’t know what is done and what needs to be done?

The point here is not to educate your audience, but rather to provide them with the tools needed to understand your proposal. A common mistake is to explain all of the research that you did to understand your topic and to demonstrate that you really know your field. This will bore your audience, who either already knows this information or does not see why they should care. It’s more important to show where current gaps are. Cut anything that doesn’t answer the what and why of what people are doing. Your depth of knowledge will come through in your thoughtful proposal.

Justify the significance of your work

Answer the question: “What happens if your work is successful?” Again, you are trying to convince your readers either to give you funding or to work with you for three (or more) years. Convince them that your project is worth it.

Your research doesn’t have to revolutionize your field, but you need to explain concretely how it will move your field forward. For example, “Successful development of the proposed model will enable high-fidelity simulation of boiling” is a specific and convincing motivation, compared to, “The field of boiling modeling must be transformed in order to advance research.”

Justify your research plan

Identify the steps needed to overcome your identified problem/limitation. Though your PhD will evolve over time, the tasks and timeline that you identify in your proposal will continue to help determine the trajectory of your research. A good plan now can save a lot of work a few years down the road.

A strong research plan answers three key questions:

• g., “In order to engineer material properties using mesoscopic defects, it is necessary to characterize the defects, measure how they affect material response, and identify techniques to reproducibly create the defects at specific sites within a material.”
• g., “In my PhD, I will focus on developing high-speed dynamic imaging techniques to characterize transient defect states in metallic nanowires. I will then use these techniques to measure the properties of nanowires fabricated with three different processes known to produce different defect structures.”
• How will you evaluate success in each step? These metrics should be concrete and measurable! Putting the thought into metrics now will make it easier for your committee (and yourself) to check a box and say ‘you can graduate.’

Each of these questions should be supported by details that reflect the current state of the art. Technical justification is critical to establish credibility for your plan. Reference the material that you introduced in the background section. You should even use your research plan to tailor your background section so that your committee knows just enough to believe what you’re claiming in your plan.

Based on the tasks and metrics in your plan, establish specific reflection points when you’ll revisit the scope of your project and evaluate if changes are needed.

Include alternative approaches

You won’t be able to predict all of the challenges you will encounter, but planning alternative approaches early on for major methods or decision points will prepare you to make better game-time decisions when you come up against obstacles. e.g.,

I will develop multi-pulse, femtosecond illumination for high speed imaging following Someone et al. Based on the results they have shown, I expect to be able to observe defect dynamics with micron spatial resolution and microsecond temporal resolution. If these resolutions are not achievable in the nanowire systems, I will explore static measurement techniques based on the work of SomeoneElse et al.

Resources and Annotated Examples

Annotated example 1.

This is a recent MechE thesis proposal, written in the style of an IEEE paper. 1,022 KB

Research Proposal Example/Sample

Detailed Walkthrough + Free Proposal Template

If you’re getting started crafting your research proposal and are looking for a few examples of research proposals , you’ve come to the right place.

In this video, we walk you through two successful (approved) research proposals , one for a Master’s-level project, and one for a PhD-level dissertation. We also start off by unpacking our free research proposal template and discussing the four core sections of a research proposal, so that you have a clear understanding of the basics before diving into the actual proposals.

• Research proposal example/sample – Master’s-level (PDF/Word)
• Research proposal example/sample – PhD-level (PDF/Word)
• Proposal template (Fully editable) 

If you’re working on a research proposal for a dissertation or thesis, you may also find the following useful:

• Research Proposal Bootcamp : Learn how to write a research proposal as efficiently and effectively as possible
• 1:1 Proposal Coaching : Get hands-on help with your research proposal

FAQ: Research Proposal Example

Research proposal example: frequently asked questions, are the sample proposals real.

Yes. The proposals are real and were approved by the respective universities.

Can I copy one of these proposals for my own research?

As we discuss in the video, every research proposal will be slightly different, depending on the university’s unique requirements, as well as the nature of the research itself. Therefore, you’ll need to tailor your research proposal to suit your specific context.

You can learn more about the basics of writing a research proposal here .

How do I get the research proposal template?

You can access our free proposal template here .

Is the proposal template really free?

Yes. There is no cost for the proposal template and you are free to use it as a foundation for your research proposal.

Where can I learn more about proposal writing?

For self-directed learners, our Research Proposal Bootcamp is a great starting point.

For students that want hands-on guidance, our private coaching service is recommended.

Psst… there’s more!

This post is an extract from our bestselling short course, Research Proposal Bootcamp . If you want to work smart, you don't want to miss this .

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Engineering Proposals

Consulting engineers aren't the only engineers who write proposals. For instance, in academia, engineers write proposals to receive funding for their research or even to initiate a project. Some engineers produce proposals to be read and approved by management while others send proposals to specific funding agencies or clients.

Definition of Proposals

A proposal is a description of the work you will complete on a project. The details included in a proposal depend on the project's scope and who will read the document. Typically, organizations advertise a need for proposalsand consulting engineers respond to the need. However, as an engineer, you may determine that a problem exists, and therefore, propose solutions to an organization. In this case, you must first convince the agency that the problem exists before proposing your solutions.

Types of Proposals

Different types of proposals are necessary for different projects. In academia, engineers produce grant proposals or research proposals in order to receive funding from government agencies and non-profit organizations. In industry, engineers, especially consultants, write proposals or "bids." Engineers produce these proposals for the company where they are working or for other organizations.

A proposal's audience is those supporting the proposed project. The details you provide in a proposal may change, depending on your audience. For instance, if you submit a Proposal to your company's management, you may not have to include project costs or other background information. On the other hand, if you produce a proposal for an organization outside your company, you may need to provide more details. These details might include a rationale for why they should fund your project, as well as the necessary materials and costs. Before writing a proposal, you should always research your audience's background. This way, you will have a better idea about what information to include in your proposal.

General Format

You can submit a proposal in several ways, depending on your audience. For example, proposing a project to your supervisor may require a phone call or a quick e-mail. Or, you may write a short memo, outlining your ideas. On the other hand, you may have to produce a lengthy proposal that provides project background and completely describes the proposed work. Typically, you will know which format to use based on the proposal's context.

When you write a lengthy proposal, you will have to spend time conducting research before you begin writing. This research might include locating other designs and theories to refer to as examples or to critique. A proposal might also include graphics to help an audience visualize your ideas. You might incorporate other data, such as dollar figures and time schedules, so your audience knows exactly how long the project will take to complete and much it will cost them To read more, choose any of the items below:

Introduction

In the proposal's Introduction, you should provide information about the need for a proposal. In other words, here is where you state why you are writing the proposal in the first place. You should also provide an overview of what the rest of the proposal includes.

Qualifications

In the Qualifications section, you should show that you and your organization (if applicable) are skilled and capable of completing the proposed work successfully. You should view this section as a "resume" since in it, you will depict your skills and experiences. If your audience is your supervisor or other managing decision-makers, then you may not need to include this section.

In the Background section, you should depict the problem/situation that lead to your writing a proposal. Here, you should show that you thoroughly understand the problem. If your audience already knows the Background, you may not need to include this section. For example, your supervisor or other managing decision-makers may already be familiar with the specific problem. Therefore, you don't need to tell them what they already know.

Work Schedule

The Work Schedule section does exactly what its name implies: It presents the time frame in which you will complete the proposed work. This section informs your audience of what to expect from you and when. It also helps to keep you organized. If, after you begin working, you are unable to keep this schedule, you should always communicate changes in deadlines to the appropriate people.

Proposal Statement

In the Proposal Statement section, you should inform your audience of exactly what you are proposing. You should also include what you aren't proposing. For example, if you are proposing partial work on a project, state this and then verify what your work will not include.

In the Cost section, you should present what costs you anticipate your project will involve. To do this, divide your expenses into categories and provide dollar figures. For example, labor costs for each worker, materials, etc. Then, you might provide a total cost.

In the Results section, you should discuss the outcome of your proposal. The types of outcomes resulting from a proposal cover a wide range. For example, you may be creating a design, building an actual construction, or even producing a lengthy report. Be sure to state exactly what the Results will be.

The Conclusion section is similar to the ending of a cover letter. Here, you should summarize why you should be considered and how you can be contacted. You might also reiterate why you are the best person or group for the project.

Methodology

In the Methodology section, you should present how you will complete the project's work. This is similar to a Lab Report's Procedures section in that you have to discuss the steps you will have taken to reach a final goal.

Perspectives on Proposals

Dave alciatore, mechanical engineering.

Internal Proposals

"You're likely to write internal proposals if you work with a product development group in a big company. For example, you might conduct research on possible new product lines. Then, you would write a proposal to communicate that you want to pursue this product, but that it will involve testing and development. In other words, it's going to cost money. In order to get financial support, you have to write a proposal that presents your plans. This includes the benefits of the product in terms of profit."

Tom Siller, Civil Engineering

Consulting Engineers

"If you are a consulting engineer, you will work in a very competitive environment because you have to sell your services. In order to get work on a project, you have to submit a proposal or give a presentation. To do this successfully, you have to know who your client is and what that client expects."

John Mahan, Electrical Engineering

Proposal Types

"Engineers write many different types of proposals. Sometimes, a proposal has to be powerful and business-oriented. Many companies don't want to look too far into the future, not even past two years. So, you have to be very specific and down to earth. You have to tell them when exactly you will complete the work. In Phase One, you'll do x. In Phase Two, you'll do y. You should also include the benefits gained during each phase."

Citation Information

Dawn Kowalski. (1994-2024). Engineering Proposals. The WAC Clearinghouse. Colorado State University. Available at https://wac.colostate.edu/repository/writing/guides/.

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FIVE STEPS FOR CRAFTING A DOCTORAL RESEARCH PROPOSAL IN ENGINEERING DESIGN

Doctoral students are required to prepare and defend a research proposal. In this paper, we present five steps for doctoral students to identify the questions that are worthy of investigation and thence to develop a research plan and proposal. Our method involves five steps, namely, Step 1: Frame the problem Step 2: Develop a research plan Step 3: Verification and validation Step 4: Proposal template Step 5: Proposal outline We illustrate the method using the sustainable design of plug-in-electric vehicle charging stations as an example.

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Engineering Proposals: Free Template + 12 Proposal Writing Tips

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Posted by: Cinthya Soto

An engineering service proposal is a standardized document pivotal in guiding the selection of consultants. The engineering proposal is more than just a document; it’s your opportunity to showcase expertise, understanding, and value among the piles of proposals. 

Whether you’re a seasoned engineering consultant or a firm stepping into the arena of important projects, your ability to craft a compelling proposal can make all the difference in placing your business ahead of the competition. After all, in 2023 alone companies sourced 39% of their revenue from RFPs .

However, mastering the creation of such a proposal is a complex task. For those wanting to successfully navigate this process, you must be ready to grasp the fundamental concepts of engineering proposals. But what exactly does that include? 

In this blog, we’re covering everything there is to know about writing engineering proposals. From what to include in your engineering proposal and writing tips to engineering project proposal examples and a free engineering proposal template, we aim to help you create winning proposals . 

How to Write an Engineering Proposal: What to Include 

Engineering proposals serve as the critical document on which selections of engineering consultants are based. For consulting firms in the engineering sector, these proposals are the principal tool for winning new contracts. For clients or project owners, they are an invaluable resource to help them choose the best consultants. But what should be included in an engineering proposal format? 

Here are the different sections you should include in your engineering proposal: 

Cover Page 

The cover page of your engineering proposal sets the first impression. It should include the project title, the name of the organization or individual presenting the proposal, the date, and any relevant project identification details. Make sure to keep it professional and clean to reflect the seriousness of your intentions. 

Cover Letter 

The cover letter personalizes your engineering proposal. It should briefly introduce your organization, express your enthusiasm for the project, and highlight the key points that make your proposal stand out. This is your opportunity to establish a connection with the reader and encourage them to read further. 

Introduction 

The proposal introduction serves as the executive summary of your proposal. It should include an overview of your organization, the purpose of the proposal, and a summary of what the proposal will cover. 

Make sure to clearly define the problem or opportunity your proposal addresses. Essentially, the introduction clarifies the purpose of crafting the proposal. It should lay out the foundation for why the proposal is necessary. 

Additionally, the introduction should provide a concise overview of the proposal’s content. This summary needs to be engaging and offer a glimpse of the detailed descriptions to follow. It reveals your core idea and outlines the strategy you intend to use in delivering your services. Here’s an example of what a successful proposal introduction looks like:

Project Background 

This section delves into the details of the project. Describe the current situation, the specific problem or opportunity, and the objectives of the project. Providing a concise but thorough background helps the reader understand the context and the necessity of the proposed work. 

You should illustrate the issue or situation that led to the creation of your proposal. In this section, it’s important to show a thorough comprehension of the problem at hand. 

Qualifications 

In this section, highlight your qualifications and experience relevant to the project. Detail your technical expertise, prior successful projects, and any unique skills or resources that make you stand out. This section reassures the client that you are capable of handling the project. 

When writing this section, make sure to accurately highlight your skill set to emphasize your suitability for the project at hand. Consider this section as the part of your resume where you detail your skills and experiences. 

While you should showcase your expertise, It’s also important to showcase, if relevant, your company’s proficiency and ability to successfully carry out the proposed task. 

Project Team 

Typically, an engineering proposal requires including details about each team member, their specific roles, and their professional backgrounds. The collective expertise of the project team often plays a critical role in the selection of a qualified engineering consultant, which is why the “Project Team” section is extremely important. 

In this section, showcase the team that will work on the project. Ensure that every team member’s relevant experience is detailed in the proposal. Make sure to include brief employee bios in your RFP resumes that highlight each member’s qualifications and relevant experience. Just a few well-crafted sentences on such skills can make a significant difference.

The right tools can help in creating and formatting these bios to present a professional image. With a robust digital asset management (DAM) solution like OpenAsset , you can cut down on the hours spent creating resumes and employee bios for engineering proposals. 

A notable feature for employee bios is Content Assist , powered by OpenAsset’s Generative AI. It’s designed to assist users in creating project descriptions and employee bios within OpenAsset. In simple terms, Content Assist will analyze the existing data in your OpenAsset system to create original project descriptions and employee bios. 

OpenAsset and the Employee Module enhance productivity within your organization by automating the creation of employee resume documents . This helps you present your team in the best light possible and quickest way possible. 

Remember, the strength of your team and how you present your team can be a significant deciding factor in winning the proposal. 

Scope of Work 

In the scope of work , you’ll want to detail the specific activities, deliverables, and timelines involved in the project. It’s crucial for an engineering proposal to precisely outline the project scope. Given that misunderstandings about project scope are a primary cause of project issues or failures, defining the scope with as much clarity is essential to prevent and more easily resolve problems. 

Clearly outline the work that will be done, the methodologies used, and the expected outcomes. This section should align expectations and minimize misunderstandings about the project’s scope. When the scope is clearly defined, everyone involved understands the extent of work expected within the project’s framework. 

Work Schedule 

The work schedule section of the proposal does precisely what its name suggests: it monitors your work schedule. 

Provide a detailed schedule of the project, including key milestones, deadlines, and dependencies. This section maps out the timeline for completing the project and is crucial as it informs your audience about the expected timelines and milestones. 

The work schedule should be realistic and allow for some flexibility. You can enhance clarity by incorporating well-organized tables and specific time allocations. It’s also crucial to demonstrate your understanding of project management and your ability to complete the project on time. 

Including a work schedule provides a professional touch to your proposal. Should you find yourself unable to stick to this schedule once the project has begun, it’s crucial to communicate any changes as soon as possible with the relevant parties. 

Project Cost 

Undoubtedly, the cost of engineering services holds significant weight in the decision-making process. The potential consultant is expected to define costs for each team member based on suitable hourly rates and the estimated hours needed for each stage of the project, along with a summary. While engineering associations recommend choosing consultants based on qualifications above cost, the reality is that pricing remains a key determinant. 

In this section, detail the expected expenses for your project by itemizing them and assigning monetary values to each category. Break down the costs into distinct groups, such as individual labor charges per employee, material costs, and so on. Summing up these figures will provide the total cost, offering the reader a clear financial overview. 

This facilitates an informed decision-making process, allowing for a thorough assessment of different factors before committing funds. 

Write a Strong Proposal Conclusion 

The conclusion of the proposal mirrors the concluding section of a cover letter. Here, you should explain the reasons for considering you or your team as the ideal choice for the project and provide your contact information. It’s also an opportunity to reaffirm why you or your team is the most suitable candidate for the project. 

Conclude your proposal by summarizing the main points, reiterating the benefits of choosing your organization, and expressing your eagerness to work on the project. End on a positive note, inviting further discussion or questions. You want to write a compelling conclusion that will leave a lasting impression on the reader. 

Expert Engineering Project Proposal Tips 

To maximize your chances of winning projects with your engineering proposals, here are 12 proposal writing tips to keep in mind when crafting your next engineering proposal: 

1. Read the RFP Multiple Times 

Simply reading the Request for Proposal (RFP) is not enough; a deep understanding of the evaluation criteria is crucial. It’s essential to review the RFP carefully, taking in every detail beyond the basic requirements such as submission dates, formatting guidelines, and required signatures. 

This thorough examination ensures you are aligned with all the requirements, conditions, and expectations outlined in the RFP. Such attentiveness not only aids in crafting a tailored response that aligns with the issuer’s needs but also minimizes the risk of non-compliance with the RFP’s requirements. 

Moreover, upon reading a new RFP, it’s smart to draft a checklist detailing all essential criteria. This approach allows a good amount of time for you to make sure everything is included in your RFP response and allows you to request any necessary clarifications well in advance of the deadline. 

2. Do Your Research 

Undertaking comprehensive research is a cornerstone in the development of a compelling engineering proposal. This process involves gathering data, understanding industry standards, exploring the project’s context, and analyzing the potential impact of your work.

Research allows you to approach the project with a depth of knowledge that will reflect the feasibility, innovation, and planning of your proposal. It also provides a foundation for making informed decisions, identifying potential risks, and proposing effective solutions. 

In essence, the research you conduct forms the backbone of a proposal that’s both convincing and achievable. 

3. Create a Clear Proposal Format 

If you’re wondering how to draft a proposal, starting with a clear format is a great start. Maintaining a clear engineering proposal format is fundamental to creating a structured and professional document. A standardized format ensures that the information is presented in an organized manner, making it easy for the reviewers to follow and evaluate. The format typically includes a well-defined table of contents, sections with clear headings, and a logical flow of information. 

This structured approach helps display your message with precision and prevents critical elements from being overlooked. Consistency in format across various sections, such as the project background, scope, schedule, and qualifications, reinforces the overall flow of the proposal. 

A well-formatted proposal not only reflects your professionalism but also helps in communicating the seriousness and preparedness of your team for the project.  

4. Introduce Your Company’s Background 

Introducing your company with a concise background in your engineering proposal is a critical step in setting the stage for a strong pitch. This section should provide a snapshot of your company’s history, core competencies, successes, and mission as they relate to the project in question. It’s an opportunity to establish credibility and build trust with the proposal’s reviewers. 

This introduction should show the essence of your company’s identity, values, and the journey that has led to its current standing in the industry. Highlighting notable achievements, experience in similar projects, and the overarching vision can create a compelling narrative that resonates with the potential client. 

A well-articulated company background serves as the foundation upon which the rest of the proposal is built, underlining why your firm is uniquely suited for the project. 

5. Feature Your Team’s Talent 

In an engineering proposal, it’s important to select the best employees for your RFP response . Make sure to illustrate the unique skill sets, qualifications, and experiences that each member brings to the table. You can use this section to delve into the specific talents that differentiate your team from competitors. 

Detailing individual roles and how they will contribute to the success of the project not only showcases the depth of your collective proficiency but also helps build confidence in your team’s ability to deliver results. Remember to align these talents with the project requirements, demonstrating a perfect fit between your team’s capabilities and the project’s needs. 

If you’re looking to generate employee resumes in minutes that demonstrate your team’s talent, a robust DAM can help you store and manage employee profiles. A DAM for engineering like OpenAsset saves you time and resources in managing your resumes. Through the use of Generative AI, you can create project descriptions and employee RFP bios. 

6. Include Images and Graphics

Incorporating images and proposal graphics into your engineering proposal can significantly enhance its impact. Civil engineering projects typically require various diagrams, illustrations, and maps. This is because the essence of designs is best conveyed through visual representation for complete clarity. The same principle applies to proposals, where visual elements are crucial for demonstrating complex information clearly and effectively. 

Moreover, using images to communicate visually will save reading time for the client. The reader will also appreciate the amount of effort put into preparing the engineering proposal. 

Use tools like OpenAsset to seamlessly find and present visuals of projects that align closely with the prospective client’s needs or showcase your team’s qualifications. This tailored visual approach not only shows your past successes but also provides a compelling, concrete visual narrative of what you can deliver. 

Moreover, AI in DAM saves you time and resources in managing your images through AI-suggested keywords, image similarity search, AI Content Assist, and more. These features: 

• Reduce the time it takes to manually tag images
• Helps you build and expand taxonomies
• Gives you additional images to select from and use.
• Enables you to leverage Generative AI for project descriptions and employee RFP bios

Images are not just embellishments; they can be powerful testimonials of your work’s relevance and quality, speaking volumes more than words alone. 

7. Use Clear Language 

Using clear and concise language is crucial when crafting an engineering proposal. The ability to demonstrate complex ideas effectively without resorting to overly technical jargon or unnecessarily complicated explanations is a skill that cannot be overstated. 

Likewise, it’s important not to assume that the readers will be familiar with the specialized jargon of your field. Take time to research the client and the reviewing committee to grasp their expertise and knowledge base. When delving into detailed technical matters, ensure you offer sufficient background to maintain inclusivity and prevent any misunderstandings. 

Proposals should be accessible, ensuring that stakeholders, regardless of their technical background, can grasp the proposed concepts and see the value in them. 

Your team might possess attributes such as “remarkable efficiency, strong motivation, and outstanding qualifications,” yet, it’s likely that your competitors claim the same. Such language is often so overused in proposals that they become clichéd and lose their impact. 

Rather than relying on generic adjectives, prove your capabilities with concrete examples of past projects or situations that illustrate your skills in action. Even more compelling would be citing testimonials or endorsements from previous clients who can vouch for your expertise. Here’s what that could look like in your proposal:

Additionally, avoiding excessive language not only helps in maintaining the reader’s attention but also demonstrates your ability to communicate efficiently. The proposal should be as concise as possible without sacrificing completeness. Every sentence should serve a purpose, whether it’s to inform, persuade, or clarify. 

8. Keep It Short 

Coming across an RFP with a large page limit or no page limit might give you the impression that you should create a significantly lengthy proposal. However, it’s best to resist this urge to write a 200-page proposal. 

Keep in mind, your potential client will be comparing your proposal with several others. A concise submission allows them to quickly discern the essential details. Overloading your proposal with text increases the likelihood of them skimming over key points — steer clear of dense paragraphs. 

A concise proposal not only respects the reviewer’s time but also enhances readability and comprehension. It’s essential to spread your message and value proposition without unnecessary elaboration. Precision in language, clarity in presenting solutions, and conciseness in your descriptions can make a powerful impact. 

Moreover, a proposal that is straight to the point is often a sign of a well-thought-out project plan and a capable, organized team that knows how to communicate. A compact and well-structured proposal often speaks volumes about your project management skills and your respect for the client’s resources and time constraints. 

9. Practice Teamwork 

A collaborative approach ensures that diverse expertise and perspectives contribute to a more robust and comprehensive document. It’s the teamwork among team members, with their unique skill sets and experiences, that can elevate the quality of a proposal. 

Working together with your team in the proposal process can lead to innovative solutions that might not surface in a siloed work environment. Teamwork facilitates thorough cross-checking, brainstorming, and problem-solving, which are essential to addressing the complex challenges typically presented in engineering projects. 

Remember, surrounding yourself with an effective team is the key to success.  A collaborative culture could be what makes you stand out from the competition. 

Moreover, highlighting the collaborative nature of your team within the proposal can also serve as a testament to your capability to work together, a quality often wanted by clients. It’s not just about the final product but also about demonstrating the process of how your team works together to achieve excellence. 

10. Proofread and Double-Check 

Proofreading and carefully double-checking your proposal is as essential as the content itself. This step ensures that your document is free from errors, which could otherwise affect the credibility of your proposal. It’s not only about catching typos or grammatical mistakes; it’s about ensuring that every figure, fact, and statement aligns with the RFP requirements and your research findings. 

A proposal that is well-edited and error-free communicates attention to detail and a commitment to excellence. It’s recommended to have multiple team members review the proposal to provide fresh perspectives and catch issues that you might have overlooked. 

Remember, a single mistake could raise doubts about the professionalism of your work and the quality of the project delivery. Therefore, rigorous proofreading and double-checking are necessary to validate the integrity and professionalism of your engineering proposal. 

11. Meet Deadlines 

Meeting deadlines is important in the context of engineering proposals. The ability to deliver on time reflects your professionalism and reliability. It’s a non-negotiable element of project management that sets the stage for how potential clients view your commitment to the project’s success. 

Planning is essential to ensure deadlines are not just met, but comfortably, allowing planning for any unexpected circumstances that might arise. Missing a deadline can have significant repercussions, from damaging your reputation to disqualification from the bidding process. 

However, it’s not just about avoiding the negative. Following deadlines can also enhance your standing with clients, as it demonstrates respect for their time and trust in your ability to manage the project effectively from the start. 

12. Submit the Proposal on Time 

Part of meeting deadlines includes submitting your proposal on time. Every RFP specifies a submission deadline that must be met. Contrary to project deadlines, which may be subject to change during a project, the cut-off date for proposal submission is non-negotiable. 

Physical submissions of hard copy proposals are often marked with an actual time stamp upon receipt. If that timestamp shows your submission arrived even one second past the deadline, it will unfortunately be too late. 

With the rise in digital submissions, the strict adherence to deadlines continues. Considering potential issues like slow upload speeds or internet disruptions, it’s wise to plan additional time when submitting proposals electronically. 

Make sure it’s clear how the proposal will be submitted so there are no surprises. You should also ask for help when it’s needed, especially if you are facing roadblocks and don’t have much time left. 

Moreover, building buffer time for reviews and potential revisions is a wise strategy. Proposal writing often shows that tasks tend to extend beyond anticipated time frames. Whether you run out of printing paper or a team member makes a last-minute change, you need to be prepared. Therefore, allowing yourself a generous timeline for the preparation and submission of the final documents can mitigate the risk of missing the deadline. 

Meeting deadlines reflect your professionalism and reliability, which are critical factors in the selection process. It demonstrates your commitment to the project timeline and sets the stage for the timely execution of the work ahead. Engineering proposals are also an investment of time and money and if you miss the deadline, this investment is wasted. 

Additionally, a punctual proposal suggests that your project management and organizational skills are well-tuned, giving potential clients confidence in your ability to deliver results within the specified timeframe. 

Free Engineering Proposal Template 

At OpenAsset, we want to provide you with valuable resources to help pave the way toward success. That’s why we’re providing a free engineering project proposal template to inspire your proposal writing journey. 

Use OpenAsset for Your Engineering Services Proposal 

Leveraging a robust DAM, like OpenAsset , in your engineering proposals is a game-changer. OpenAsset streamlines the process of incorporating high-quality images and project data that represent your team’s past achievements and expertise. 

By using OpenAsset, you can create a visually impactful and content-rich proposal that stands out. It not only saves valuable time by organizing your assets efficiently but also ensures that you present a polished, professional, and tailored proposal to your potential clients. 

OpenAsset’s DAM solution makes AEC proposals simpler, faster, and more successful. That’s why 99% of customers renew. Leverage OpenAsset to elevate your proposals and effectively demonstrate why your team is the ideal choice for any AEC project.  

Ready to start creating engineering proposals that will set you apart? 

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How to Create Winning Proposals

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Mechanical Engineering

How to Write a Project Proposal

Contents of proposal.

A recommended template for an MS project or thesis proposal is provided at the following link, from which you can make a Google Docs copy or download a Microsoft Word file:

ME 295 and ME 299 Proposal Template

Proposal Approval Process

The project proposal must be written so that it provides a strong evidence of a student’s thorough understanding of the topic and the capabilities to carry out the work successfully. There are three levels of approvals and signatures required to ascertain that the student in fact has the understanding and capabilities to complete the project successfully. First, the proposal is reviewed, evaluated, and signed by the advisory committee. Next, the signed Proposal Evaluation Form  is attached to the proposal, along with the completed Proposal Cover Sheet and submitted to the ME office for approval and signatures of the Graduate Advisor and the Department Chair. Refer to the Projects and Thesis tab for proposal deadline.

See our detailed instructions [pdf] for submitting the project proposal in DocuSign to help guide you through the process. 

Proposal Deadline

The proposal must be approved by the advisory committee, the Graduate Advisor, and the Department Chair prior to the university deadline for adding a course, usually the second week of February for the Spring semester and the second week of September for the Fall semester. The add-code for the first term project is issued by the ME office only after the approved project proposal has been received. Failure to meet the deadlines can delay your graduation.

Sample Proposals

The following are some representative examples of project proposals. Your proposal may have additional requirements depending on your project committee chair.

• Sample 1 (Bicycle brake)
• Sample 2 (Collapsible cup)
• Sample 3 (Object detection)
• Sample 4 (Metamaterial)
• Sample 5 (Battery)

Engineering Project Proposal

Engineering project proposals are written for a variety of reasons. There are some engineering project proposals that are made to persuade potential sponsors, funding agencies, and/or creditors. There are also some engineering project proposals that allow the plans of engineers to be considered and approved by the management of the firm where they work for or the clients who would like to get their services. With these being said, an engineering project proposal is actually like a concept proposal  in a way that it reflects and presents the specific ideas of an engineer for a particular engineering project.

An engineering project proposal must be aligned with the kind of engineering project that you would like to be a part of. It should also be the result of either a request or an existing issue, concern, or problem. To guide you in developing a clear and goal-derived engineering project proposal , we have listed several downloadable examples of engineering project proposals that are used in various activities and programs.

15+ Engineering Project Proposal Examples

Engineering proposal example.

• Google Docs

Size: A4, US

Engineering Project Proposal Template

Engineering Student Project Proposal Template

• Apple Pages

Size: 115 KB

Engineering Project Execution Plan Template

Size: 26 KB

Engineering Project Scope Template

Size: 162 KB

Free Engineering Project Roadmap Template

• Apple Keynote
• Google Slides

Size: 66 KB

Civil Engineering Project Manager Resume Template

Size: 98 KB

Agricultural Engineering Project Proposal Example

Size: 44 KB

Software Engineering Project Proposal Example

Size: 133 MB

Engineering Research Project Proposal Example

Industrial and Systems Engineering Project Proposal Example

Size: 201 KB

Chemical Engineering Project Proposal Example

Size: 601 KB

Computer Engineering Project Proposal Example

Size: 551 KB

Mechanical Engineering Project Proposal Report Example

Size: 350 KB

Engineering Project Proposal Format Example

Size: 187 KB

Mechanical Engineering Project Proposal Example

Engineering Project Proposal Example

How to Impress the Target Audience of Your Engineering Project Proposal

If you think that only consulting engineers are bound to develop an engineering project proposal, then you may want to think again. There are different engineering positions that are also required or tasked to come up with an engineering project proposal may they be in their own fields of engineering expertise or in the fields of education, advanced research, and academics.You may also see project proposal outlines .

Since there are a lot of engineering project proposals that you can create, expect that there are also different types of audiences that you need consider whenever you plan to develop this document. Here are some of the ways on how you can impress the target audience of your engineering project proposal:

1. Make sure that you will properly define the entities who support the project that you are proposing. Knowing how your audience is can give you more idea on how you can properly present the engineering project proposal in a more appealing manner. You may also see short proposals .

2. You can rely on templates and references when making an engineering project proposal but make sure that the content and discussion presentation that you will come up with must be aligned with the needs, requirements, and expectations of your audience. With this, you can identify the set quality standards that you need to meet or even exceed for the engineering project proposal to be approved. You may also see non-profit proposals .

3. Know the scope and limitations of the information that you will include in the engineering project proposal based on the type of audience for your presentation. As an example, there is a big difference with the way you present engineering project proposals to external entities and the company that you work for. External entities like clients and investors need more information about your services and offers, while your company requires the proper budgeting for raw materials and engineering workforce. You may also see fundraising proposal .

4. Be aware of the background of your clients. This will help you know the information that are essential to be included in the specific engineering project proposal that you will make. In comparison to a management plan, your engineering project proposal must also be based on how you would like your target audience to perceive the potential of your recommendations for development.

Engineering Project Proposal Content

An engineering project proposal may be the result of a proposal request from clients or the management. It can also be a direct proposition from an engineer presenting potential solutions to problems or current conditions. No matter what the purpose of the proposal writing or the creation of an engineering project proposal is, you have to keep in mind that it is important for you to ensure that you will create a comprehensive, well-detailed, and organized document. Here are some necessary information that are commonly found in an engineering project proposal:

1. Have a proposal statement that can define the scope and limitations of the engineering project proposal. You have to develop a limit to what you are proposing so that project expectations can be set. Minimum requirements can also be expected to all stakeholders of the potential engineering project if this will be done. You may also see budget proposals .

2. Write an introduction for the engineering project proposal. A brief discussion of the proposal’s description can present the need for the engineering project. This part of the engineering project proposal can also help you to present the purpose not only of the project but the usage of the proposal document as well.

3. Present the situation that made you decide to write the engineering project proposal. Are you required by the management of the business? Are you presenting the proposal to a client or another organization? Are you trying to recommend or suggest an engineering project that can benefit a target community? Knowing the purpose of the engineering project proposal can make it easier for the audience to understand the need for the proposed project to be implemented. You may also see research proposal .

4. Have a representation of the methodology that you will follow should the proposal be approved. List down all the processes that the project team and other stakeholders will undergo so that your target audience can be aware of these activities.

5. Create a work schedule for the engineering team. Present the specific time frame that you would like to execute so that you can make sure that the project is time-bound. Proposed work processes that are within specific time schedules can make the engineering project proposal more impressive. You may also see proposal memo examples.

6. Have a financial plan for the engineering project that you are proposing. List down all the cost that the business or the clients need to prepare for so that the project can be implemented. Before creating the proposal, you can already ask for the budget range of entities so that you can have a guide when selecting suppliers, contractors, and workforce providers. You may also see security proposal .

7. It is highly recommended for you to write a few information about your credentials or the milestones of your company. This is a great way to present your credibility and trustworthiness. Moreover, it can reflect your ability to provide all the deliverable that can make the project be created with quality standards.

8. Be particular with the discussion of your desired results. You have to stick with the purpose of the engineering project. Moreover, you always have to be specific when discussing this part of the engineering project proposal as this is a big factor when considering the approval of your proposal. You can also come up with a conclusion that can summarize the entire engineering project proposal discussion. You may also see development project proposals .

Suggestions, Tips, and Recommendations in Making an Engineering Proposal Project

Engineers create project proposals to present the professional work that they would like to propose so that the particular needs of different stakeholders can be provided. With the range of engineering processes that have varying practices and natures of circumstances, there are different engineering project proposals that can be created. For you to come up with a concise and comprehensive engineering project proposal, listed below are some of the suggestions, tips, and recommendations that you can refer to. You may also policy proposals .

1. Maintain organization when presenting the discussion within the engineering project proposal. You have to ensure that your audience is aware of what they can expect from you especially when it comes to work processes, quality metrics, deliverable, and timetable attainability. You may also see service proposals .

2. Use  proposal examples  and templates as references especially those that are aligned with the exact kind of engineering proposal project that you need to make. Always remember that you should not just look into the content of the document but the proper presentation of these information as well.

3. Know the tone of the discussion that you will incorporate in the engineering project proposal. Do you want the engineering proposal project to be engaging and persuasive? Would you like it to be business-oriented? Different writing approaches can be done depending on the kind of engineering project proposal that you are bound to make. You may also see professional proposals .

Having the right mind-set and the goal to finish an outstanding engineering proposal project can help you a lot when it comes to preparing the document. Again, feel free to refer to downloadable examples, tips, and guidelines so that you can be more efficient in using your time and effort when creating an engineering proposal project.

Proposal Maker

Text prompt

• Instructive
• Professional

Generate a proposal for a new school recycling program

Compose a proposal for a school field trip to a science museum.

Research methods in engineering design: a synthesis of recent studies using a systematic literature review

• Original Paper
• Open access
• Published: 16 January 2023
• Volume 34 , pages 221–256, ( 2023 )

Cite this article

You have full access to this open access article

• David Escudero-Mancebo   ORCID: orcid.org/0000-0003-0849-8803 1 , 2 ,
• Nieves Fernández-Villalobos   ORCID: orcid.org/0000-0003-2559-0652 1 , 3 ,
• Óscar Martín-Llorente   ORCID: orcid.org/0000-0001-9200-5797 1 &
• Alejandra Martínez-Monés   ORCID: orcid.org/0000-0003-3201-0345 2  

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The relation between scientific research and engineering design is fraught with controversy. While the number of academic PhD programs on design grows, because the discipline is in its infancy, there is no consolidated method for systematically approaching the generation of knowledge in this domain. This paper reviews recently published papers from four top-ranked journals in engineering design to analyse the research methods that are frequently used. The research questions consider the aim and contributions of the papers, as well as which experimental design and which sources of data are being used. Frequency tables show the high variety of approaches and aims of the papers, combining both qualitative and quantitative empirical approaches and analytical methods. Most of the papers focus on methodological concerns or on delving into a particular aspect of the design process. Data collection methods are also diverse without a clear relation between the type of method and the objective or strategy of the research. This paper aims to act as a valuable resource for academics, providing definitions related to research methods and referencing examples, and for researchers, shedding light on some of the trends and challenges for current research in the domain of engineering design.

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Questionnaire Design

Introduction to Design Science Research

How to conduct systematic literature reviews in management research: a guide in 6 steps and 14 decisions

Avoid common mistakes on your manuscript.

1 Introduction

Doctoral studies have a long tradition in higher education systems (Bogle 2018 ). Doctoral studies are highly relevant because they are considered as a key for technical development and industrial excellence in developed countries. Normally, a PhD diploma is compulsory for pursuing and it is highly valued for getting involved in research projects in companies. The goal of doctoral programs is to provide postgraduates with competences for the generation of knowledge in a given domain. The means to generate knowledge depends on the area, being research methods and techniques potentially different, and evolving in parallel with the development of the domain. In young domains such as Engineering Design, the discussion about which research procedures and paradigms should be employed is still open.

Simon ( 1996 ), in his book The Science of Design ,  defined design as a search for an optimum in a space of alternatives that take into account the specifications and restrictions of a given problem. Hatchuel ( 2001 ) highlighted limitations of Simon’s position discussing that designing cannot be reduced to taking decisions among a bounded set because the number of concepts related to the problem and the possible number of decisions to be taken could be expandable and uncountable, not only due to human creativity but also to social interaction. (Subrahmanian et al. 2020 ) place Simon and Hatchuel’s approaches in a historical timeline that describes different models of how designing is understood, evidencing the challenges for research design as a discipline that defines a common language that includes the impact of context and users in designing, in addition to the problems.. Probably due to the youth of design as a research discipline, or due to its socio-technical nature, it does not yet have a consolidated research methods and techniques. Blessing and Chakrabarti ( 2009 ) proposed the DRM (Design Research Methodology) motivated by “ frustration about the lack of a common terminology, benchmarked research method and a common research methodology in design”. Through the analysis of recent research papers, this work has the aim to confirm how these visions about research in engineering design are projected in current state-of-the-art publications.

Since the work of Blessing and Chakrabarti, there have been some relevant proposals that have shed light on different aspects of the global design research landscape. Koskinen et al. ( 2011 ) proposed the term ‘constructive design research’ and presented alternatives to integrate research within the practice of design. Joost et al. ( 2016 ) used the term ‘design as research’ in a volume that compiled discourses of experts about questions on design research and its relationship with other disciplines. Vaughan ( 2017 ) presented a survey that collected different points of view related to doctoral education in the opinions of design graduates about practice-based research design. Redström ( 2017 ) presented an essay about how to develop theory -knowledge- by practice, experimentation and making -design. These works are a multi-faceted compendium of practical experiences and visions of experts on how to perform activities related to research in the domain of design. Although many examples and discussions presented in the cited books focus on the topic of research through/by design, rather than on research in engineering design, all of them agree on the relevance of research into the design due to the increasing number of PhD programs that could benefit from background knowledge about this topic. In this paper, we present an alternative approach to shed light on the relations between research and design: instead of collecting the personal visions of experts, we summarise and classify research papers on research in Engineering Design in terms of aims and contributions, methods and approaches, data collection techniques, and research instruments used for the collection of data. To this end, we have carried out a systematic review of the literature on research in engineering design. The overarching research question (RQ) that drives the review is: What is the current landscape of research methods in engineering design?

Access to doctoral studies normally requires candidates to have a Master’s degree in which they have taken courses about research methodologies. Doctoral studies normally culminate with the defense of a PhD thesis in which postgraduates have to show their capabilities to generate knowledge in a specific field. Submitting a PhD thesis that includes activities previously reviewed in scientific journals is generally considered as a quality warranty of the research performed by the student. Although publishing journal papers is not the only way to assess the excellence of the research work performed in a PhD thesis, the quasi-exponential increase of scientific publications we are witnessing (Tenopir and King 2014 ) indicates that it is probably becoming a universal standard for rating the quality of research. Therefore, being aware of the kind of works published in scientific journals related to engineering design could be of outstanding importance for scholars who have to configure the contents of the courses related to research methodologies in this field, as well as for PhD supervisors and students to focalize efforts for being more productive in terms of publications. The analysis of scientific papers about research in engineering design performed presented in this paper aims to contribute to this aim.

There are many possible ways to analyse, categorise or classify research works because there are many dimensions of analysis. Creswell ( 2009 ) presents a classical distinction between (1) quantitative, (2) qualitative and (3) mixed-methods (combining qualitative and quantitative research methods). For quantitative methods experimental designs, non-experimental design are distinguished. For qualitative, narrative research, ethnographic research, phenomenological research, grounded theory and case study research are distinguished. For mixed-methods, sequential, concurrent and transformative methods are distinguished. Blessing and Chakrabarti ( 2009 ) identified the following ones: (1) paradigm, that includes empiricism (Randolph 2003 ; Solomon 2007 ) and ethno-methodology (Atkinson 1988 ), methodologies, theories, views and assumptions (Kothari 2004 ); (2) aim, research questions and hypotheses; (3) nature of the study, including observational vs interventional (Thiese 2014 ), comparative vs non-comparative; (4) units of analysis; (5) data collection methods including recordings, interview, questionnaires (De Leeuw 2008 ); (6) role of the researcher (Fink 2000 ); (7) time constraints, duration and continuation of the research process; (8) observed processes including layout drawing, prototype or product; (9) setting referring to laboratory or field research (Paluck and Cialdini 2014 ); (10) tasks including type and complexity and nature; (11) number of cases, case size and participants (Diggle et al. 2011 ); (12) object of analysis distinguishing objects, companies, projects, documents… (13) coding and analysis, analysis and (14) verification methods (Brewer and Crano 2014 ); or (15) findings, that is, statement models or conclusions resulting from the study. Reich and Subrahmanian ( 2021 ) use the PSI framework (Problem, Social and Institutional space) to analyse and categorise research design works focussing on dimensions related to the problem being addressed concerning (1) disciplinary, (2) structural complexity and (3) knowledge availability; dimensions related with who is included in designing concerning (4) the perspective required to formulate the problem, (5) the inclusion of participants in the design process and the (6) capabilities of the design team; and finally dimensions related with how designing is executed taking into account (7) the ties or connections between actors, (8) the accessibility to knowledge and (9) the institutional complexity (Reich and Subrahmanian 2020 ). The dimensions presented by Blessing and Chakrabari have the ambition to classify different aspects to be taken into account when research in engineering design works are tackled. The dimensions proposed by Reich and Subrahmian are complementary and arise when they analyse the factors influencing success in engineering design projects. When analysing papers, some of the details related to some of the listed dimensions could be missing in the descriptions (timing, success validation etc.) so that we had to devise alternative proposals.

Our analysis pivots around the division between empirical qualitative, quantitative research and mixed-methods proposed by (Creswell 2009 ). This classification was complemented with analytical research methods, as specified by (Adrion 1993 ), cited by (Glass 1995 ) (defined in Sect. 2.2). From this germinal division, data-collection methods, strategies, and contributions of the studies are reported in cross-analysis tables. We aim to identify the main goals and results pursued or obtained by researchers (dimensions 2 and 15 of Blessing and Chakrabarti 2009 ), the strategies of enquiry and methodologies they follow (dimensions 1, 3, 9, 10 of Blessing and Chakrabarti 2009 ), and which data sources and instruments are most (and least) commonly used (rest of dimensions of Blessing and Chakrabarti 2009 ) in the domain of engineering design.

The structure of the document is the following: First, we present the review method and the categories used to classify the papers. We then present the quantitative results of the number of papers in each of the categories and the cross relations of the different classes, shedding light on the relative weight of each of the qualitative and quantitative approaches and the most frequent data-collection methods used. Next, we discuss the usefulness of the obtained results for academics and professionals interested in research design and the paper ends with the conclusions. Complementary material is provided with a brief description of each of the analysed papers.

We follow Kitchenham et al. ( 2009 ) as a guideline for performing the systematic review. The nature of the research question did not suit a usual search in the databases, as we were interested in analysing the approaches to research published in the field of engineering design. For this reason, we focused on identifying papers published in relevant journals in the field. The data sources are journal papers in the field of engineering design.

A simple search in the Journal of Citation Reports using the term “Design” as a key search title criterion, generates a list of 99 journals indexed in different categories. Only 80 are indexed in 2020, the rest of them in previous years. As we aimed to high-impact journals reporting research in engineering design, we focused on the journals indexed in SCIE (Science Citation Index Expanded) related to Science and Technology, discarding the 22 journals indexed in ESCI (Emerging Sources Citation Index), the 10 indexed in AHCI (Arts and Humanities Citation Index) and the 5 indexed in SSCI (Social Sciences Citation Index). Among the 43 remaining journals indexed in SCIE, 13 of them correspond to categories related to Chemistry and Biology (for example Anti-Cancer Drug Design or Molecular System Design & Engineering ) 11 of them to Computer Science or Electrics (for example Design Codes and Cryptography or Computer Aid Design ); 3 with Mathematics (for example Journal of Combinatorial Design ) and 2 with Building ( Architectural Engineering and Design Management or Structural Design of Tall and Special Building ). Closer to engineering design are the 14 remaining journals: 4 indexed in Mechanics Journal of Mechanical Design, Mechanics Based Design of Structures and Machines, Journal of Advanced Mechanical Design Systems for Manufacturing and Journal of Strain Analysis for Engineering Design ), 4 related to Materials ( Materials & Design, Proceedings of the Institution of Mechanical Engineers, International Journal of Mechanics and Materials in Design and Road Materials and Pavement Design ); and 2 related with vehicle design ( Journal of Ship Production and Design , and International Journal of Vehicle Design ). In spite of being closer to the topic of research in engineering design, we discarded these journals for being too specific. The remaining 4 journals were: (i) Design Studies (DS), (ii) the International Journal of Design (IJD), (iii) the Journal of Engineering Design (JED) and (iv) Research on Engineering Design (RED). Table 1 shows that these journals share the category denominated “Engineering Multidisciplinary”. In this category, there are 6 journals that have the term “Design” in the title, the four selected plus International Journal of Technology and Design Education (also indexed in SSCI), Artificial Intelligence for Engineering Design Analysis and Manufacturing (also indexed in Computer Science) that were discarded for being specialized in education and in artificial intelligence with applications in engineering design, respectively, and therefore, out of the focus of our research.

Each of the selected journals declare in their presentation their aims and audience: RED focuses on design theory and methodology, DS focuses on design processes, JED focuses on different aspects of the design of engineered products and systems, and IJD publishes research papers in all fields of design. The audience of DS, JEC and IJD is broader than the one of RED, which focuses on mechanical, civil, architectural, and manufacturing engineering. Overall, the four journals constitute a rich and representative sample that includes works of diverse nature, applying a variety of research methods and approaches to different problems in the context of research in engineering design.

Sample selection in systematic literature reviews must be structured, comprehensive, and transparent (Hiebl 2021 ). To comply with these three requirements, we established a recent and limited temporal window and applied random selection to select the sample. We collected 17 papers from each journal, as 17 is the number of papers available in one of the journals under analysis (IJD) and we chose to use the same number of papers per journal to avoid bias (i.e., giving more importance to one journal than another) in the study. For the journals with more than 17 papers in the period of analysis, random selection was applied. We focused on papers published between November 2018 and November 2019, which was the most recent available time window when this work was started.

This methodology led to a final total of 68 papers. We followed a collaborative team-coding approach (Saldaña 2021 ). Papers were selected and assigned randomly to a pair of reviewers. Each reviewer coded two papers every two weeks. Disagreements and new code proposals were resolved in periodic meetings involving the four researchers/authors. The first author of this paper played the role of “codebook editor” (MacQueen and Guest 2008 ), updating the code list after the meetings and he used the data from the analysis to build the final tables and present the resulting themes derived from the study.

With the aim of answering the general question of this review, RQ:, “What is the current landscape of research methods in engineering design?”, we focused on the following more specific sub-questions:

What are the research goals pursued by the analysed works?

What are the main experimental approaches found in the reviewed papers?

What data collection methods are employed in the reviewed works?

Which instruments are normally used to collect these data?

To answer these questions, we followed an anticipated data condensation approach (Miles et al. 2020 ). We defined four overarching topics corresponding to the research sub-questions: aims and contributions of the research; research approach; data collection techniques; and instruments for the collection of data. For each topic, we defined a set of categories, based on our revision of engineering design methods (see Sect. 2). During the iterative coding work, emerging categories were included when required. The new categories were used to re-codify all the works. This combination of deductive and inductive coding enabled us to derive new meanings from the data.

In the rest of this section, we present the categories that were identified in the analysis under each topic. Appendix shows complementary information with representative examples of the categories.

2.1 Aims and contributions

Concerning the aims/contributions of the research (RQ1), we started from an empty list of research targets which was enriched as the number of reviewed papers increased. Finally, the following research goals were identified through the coding process:

To study or propose a methodology, that focuses on papers whose main objective is to study an existing design methodology by analysing its validity in works that propose a new design methodology or that develop a part of it more deeply.

To delve into a given aspect of design, which includes papers that focus on exploring an aspect of a design (team communication, sketching, generation of ideas, materials...) or that explore one area of design that is recognised as challenging (social design, inclusive design, ecological design...).

To design, develop, or test a specific product , which includes those papers that set out the process of creation or development of a specific product or a group of them. Some of these works describe the overall process of creating a product, and others focus on a specific phase of its development (research, ideation, testing, and validation).

To make recommendations or propose guidelines, which include articles whose main aim is to systematize the results of their research to provide advice, either at a methodological level or in the design of new products.

Proposing a theory includes those articles that use logical reasoning or mental operations, such as imagination, intuition, abstraction, and deduction, with the aim of enunciating concepts or creating models, explanations, or theories about the phenomena under study.

Proposing a framework of analysis or a taxonomy that enables concepts or objects to be classified into categories.

More than one code could be assigned to each of the papers. This could be the case of a paper that aims to develop a specific product and ends by proposing guidelines.

2.2 Research approach

Concerning experimental approaches found in the reviewed papers (RQ2), as explained in the introduction, we propose the use of the distinction between quantitative, qualitative, mixed, and analytical research methods, defined as:

Quantitative empirical studies are those that aim at testing theories by examining relationships between variables, based on the collection of numerical data which is analysed using statistical procedures.

Qualitative empirical studies are those that aim at exploring and understanding in depth the meaning that individuals or groups give to a problem. They usually involve the collection of non-numerical data obtained in the participants’ settings and follow inductive analysis approaches in which the researchers interpret the meanings of the collected data.

Mixed-methods studies are those that combine both quantitative and qualitative approaches at diverse levels (data sources, analytical methods, etc.), so that the overall study is stronger than using each of the two approaches (i.e., quantitative, or qualitative) separately.

Analytical studies are those that focus on the formalization of a model and its demonstration. They start out by proposing a formal model with a mathematical formulation, derive results using deductive approaches, and, if possible, compare these results with empirical observations.

With respect to quantitative empirical studies, we subcategorize them into experiments, quasi-experiments and non-experiments, depending on the way the subjects of interest are assigned to an experimental group or to a control group:

Experiments: the assignment of subjects to the experimental or to the control group is random.

Quasi-experiments: there is not a random assignment of a subject to the groups.

Non-experiments: there is not control on the grouping of subjects.

When a known qualitative strategy of inquiry is used, it is also tagged. According to the definition proposed by Creswell ( 2009 ), strategies of inquiry are types of methods, designs or models that provide specific direction for procedures in a research design.

Ethnographic research documents the beliefs and practices of a particular cultural group or phenomenon in its natural environment from the perspective of insiders (Lapan et al. 2012 ). The researcher stays on site for a considerable amount of time to analyse practices and behaviours of groups, by observing, interviewing and (sometimes) participating in the process under analysis. Very popular in social sciences, it is also used in architecture (Cranz 2016 ).

In phenomenological research , the researcher identifies the essence of human experiences about a phenomenon as described by participants, while the researcher sets aside his or her own perspective (Wilson 2015 ).

Grounded theory is a strategy of inquiry in which the researcher derives a general theory grounded in the views of participants, involving the use of multiple stages of data collection (Jørgensen 2001 ).

Hermeneutics inquiry focuses on disclosing how participants’ interpretations of a phenomenon determine the way they live in the world (Stigliano 1989 ). This technique is popular in architecture (Pérez-Gómez 1999 ) .

Case study research is an empirical strategy of inquiry that investigates a contemporary phenomenon within its real-life context (Yin 2009 ). It uses descriptions of programs, events, or other phenomena to construct a complete portrayal of a case for interpretation and possible action (Lapan et al. 2012 ).

Eikeland ( 2006 ) describes different approaches to action research that involve applied research, moving experimentation from laboratories to field, inviting the subjects of research to join the community of researchers and involving practitioners in research with the insistence of thinking through personal practices. Action research is a very popular approach in social sciences (Stringer 2008 ; Clark et al. 2020 ) and it is also proposed for architecture (Herr 2015 ) and for the practice of product design (Swann 2002 ). This method is related to the terms research-through-design, practice-based-design research or research-by-design (Redström 2017 ; Vaughan 2017 ), that has been discussed to be a kind of action research in works like (Kennedy-Clark 2013 ; Motta-Filho 2021 ).

Case study is generally used for exploratory research or for pre-testing some research hypotheses (Blessing and Chakrabarti 2009 ). Action research requires a high degree of flexibility and is usually qualitative, data-driven, participatory, and makes use of multiple data sources. Case study and action research also appear in the following criteria of classification, following the proposal of Blessing and Chakrabarti ( 2009 ) referring to data-collection techniques.

2.3 Data-collection techniques

In this subsection, we present the list of data-collection techniques we have tagged, to analyse what is proposed in RQ3. Following the list of data-collection methods presented in section A.4 of Blessing and Chakrabarti ( 2009 ), excluding experiments, case studies and action research we prefer to include in the list of inquiry research strategies presented in the previous subsection.

Observation is a technique in which the researcher records, in real time, what is happening, either by hand, recording it or using measuring equipment. As Blessing and Chakrabarti ( 2009 ) explain: ‘The quality of observational data is highly dependent on the skill, training and competency of the observer’ (Blessing and Chakrabarti 2009 ). Observations are the main source of data in ethnographic studies (see Sect. 2.1), but this strategy is also commonly used in social sciences (Creswell 2009 ) and in visual design (Goodwin 2000 ), architecture (Cuff 1992 ) and product design practice (Wasson 2000 ).

Simultaneous verbalization refers to the situation in which the participants speak aloud while using a system, with the aim of providing information about the cognitive behaviour of the participants, which may not be obtained through normal observation (Ohnemus and Biers 1993 ). Often used to analyse problem-solving behaviour, its most important feature is the real-time aspect. Simultaneous verbalization sessions usually last a few hours and never more than a day, due to the effort required by both the participants and the researchers in their corresponding analysis. Although audio recordings are sometimes used to record simultaneous verbalization, they are understood as inappropriate for a process such as design, which usually involves drawings and gestures, so video recordings are considered more appropriate.

Collecting technical documents consists of obtaining technical documents related to a particular project, topic or product, from various sources (Rapley and Rees 2018 ). Analysis of these documents is often used early in a research project to understand the organisation, the background of the project and the experience of the designers. It is commonly employed in most observational studies. However, if it is used as a single source of information, it can result in such limitations as the usual lack of data on the context in which the documents were created and the reason for their content. It is, therefore, convenient to complement them with other methods such as interviews.

Collecting physical objects involves mock-ups, prototypes and other physical models that may be relevant for developing a product or testing it. The model or prototype could refer to a part of the product or the whole product. For traditional engineering research, which focuses, for example, on the analysis of product behaviour, the products are the main source of data (Blessing and Chakrabarti 2009 ). In our review, we consider those works that start collecting different objects to carry out a study on their usefulness, or on the behaviour of users, for example. The object is a general term that can refer both to drawings and physical objects. Among the former, we find all those sketches, drawings and diagrams that have emerged throughout the conception of a product or its development, or throughout a research process, which could yield important information to organise ideas and draw conclusions.

Questionnaires are used to collect people´s thoughts or opinions about a certain product, process or method (Radhakrishna 2007 ). A priori, they seem easier to use than real-time methods, such as observation or simultaneous verbalization, and they are useful to obtain data from a greater number of cases. However, some of its disadvantages, such as the time required by the participants and the potential bias of the results, must also be taken into account.

Interviews have the same purpose as the questionnaires but are carried out face-to-face (King et al. 2019 ). Sometimes they are not carried out individually but using a group dynamic known as focus group: a group interview that mixes aspects of interviews and observations, as it provides information from the study of the interactions between participants. Focus groups can provide richer information than interviews, but they can have a negative effect on the contribution of specific participants.

2.4 Instruments for the collection of data

Data collection methods are supported by instrumentation. This section describes the categories we found to respond to RQ4, exposing the instruments that are normally used to collect these data. Independently of the strategy of inquiry applied, there are several instruments that are used to keep records of the observations. These recordings are important to keep evidence and to enable the reproducibility of the analysis. We tagged the papers depending on the use of classical audio, video and image recordings and the more recent technique of eye tracking (Bergstrom and Schall 2014 ).

In experiments and case studies, we are also interested in physical measurements that are used to objectify observations.

When questionnaires and/or interviews are the data-collection techniques, we tagged who is the attendee, distinguishing between stakeholders , users of products or participants (observed people) in the research and experts or designers. We also found it relevant to tag when the study uses workshops as a means to obtain information.

The last topic of interest that has been tagged is the fact that the research work uses simulation algorithms or tools as a source of information. We use this tag when the simulation tools are a fundamental part of the research, as it provides the information analysed in the paper (Behera et al. 2019 ), or because the tool or the algorithm itself is the main contribution (Mathias et al. 2019 ).

3.1 Aims and contributions of the reviewed papers

Table 2 shows the codes assigned to each of the papers analysed. This section summarises the results related to RQ1 (research goals). As shown in Table 2 , most of the works focus on methodologies or on the analysis of a specific aspect of the design processes. The presentation of a product and the building up of knowledge with taxonomies, guidelines, theories, or reviews, are exceptions.

Five papers propose a theory: (Comi et al. 2019 ) present the concept of shared professional vision; (Benavides and Lara-Rapp 2019 ) present the principle of weaker dependencies in axiomatic design; (Martinec et al. 2019 ) introduce the state-transition model (synthesis, analysis, evaluation) in conceptual design and Lloyd ( 2019 ) defends the theory of the social turn in design, Aktas and Mäkelä ( 2019 ) focus on the relation between craft, materials, makers.

Six works focus on the evaluation of a specific product: a software product in Takahashi et al. ( 2018 ) and Belkadi et al. ( 2019 ); or physical objects in the case of Roesler et al. ( 2019 ), Hyysalo et al. ( 2019b ) and McKinnon and Sade ( 2019 ).

Concerning the works related to methodologies, we find papers that propose a method based on analytical methods or algorithmic solutions such as those related to axiomatic design (Chen et al. 2019a ) and those related to such methods as research-through-design, where the importance of the method followed is prominent in the study (Tsai and Van Den Hoven 2018 ; Hyysalo et al. 2019b ; McKinnon and Sade 2019 ; Hanrahan et al. 2019 ); or methodologies for product development such as Daalhuizen et al. ( 2019 ), with emphasis on different aspects such as work in groups (Gyory et al. 2019 ), sustainability (Santolaya et al. 2019 ) or democratised design (Hyysalo et al. 2019a ).

A good number of papers present frameworks of analysis or classifications with different purposes. Bresciani ( 2019 ) for classifying visualization dimensions, McDonald and Michela ( 2019 ) to classify moral goods, Roy and Warren ( 2019 ) for card sets, Park-Lee and Person ( 2018 ) identify three practices on briefing, Vegt et al. ( 2019 ) deduce 3 types of invasiveness evoked by the rules in gamified brainstorming, Valverde et al. ( 2019 ) classify the type of feedback in automotive push buttons, Cooper ( 2019 ) presents the five waves in design research, Luck ( 2019 ) describes the framework to distinguish between design, design research, architectural design research and practice, Hobye and Ranten ( 2019 ) present five behavioural strategies for interactive products and Van Kuijk et al. ( 2019 ) presents a framework to analyse usability concepts of electronic products and Petreca et al. ( 2019 ) for analysing the relation between sensors and textile. We also include in this category the papers related to ontologies, that are used to represent knowledge.

Proposing recommendations is a common result in the analysed research papers, including a variety of themes such as recommendations on the use of guidelines by new designers (Reimlinger et al. 2019 ); the use of specific materials (Genç et al. 2018 ; Pedgley et al. 2018 ; Aktas and Mäkelä 2019 ; Petreca et al. 2019 ); how to orient future studies on the use of mobile technology by elderly people (Li and Luximon 2018 ), or about design and poverty (Jagtap 2019 ) or ethnographic studies in developing countries (Wood and Mattson 2019 ); appliance design (Selvefors et al. 2018 ); use of games in brainstorming (Vegt et al. 2019 ); or specifying requirements (Morkos et al. 2019 ). Cooper ( 2019 ) proposes interprets the history of design research through five waves.

The most frequent type of works delve into a particular aspect of product design such as sketching (Sung et al. 2019 ; Self 2019 ), prototyping (Menold et al. 2019 ; Mathias et al. 2019 ), material (Pedgley et al. 2018 ; Aktas and Mäkelä 2019 ; Barati et al. 2019 ; Petreca et al. 2019 ), interaction (Hobye and Ranten 2019 ; Valverde et al. 2019 ), briefing (Park-Lee and Person 2018 ), working in groups (Graeff et al. 2019 ), iterations and testing (Tahera et al. 2019 ; Piccolo et al. 2019 ); behavioural complexity (Hobye and Ranten 2019 ), manufacturing (Yang et al. 2019 ), or usability (Van Kuijk et al. 2019 ).

3.2 Strategies of inquiry and methodologies

This section summarises the results related to RQ2 (main experimental approaches founded): qualitative approaches are a majority, but the number of quantitative or mixed-methods studies is also relevant. Other approaches, such as the use of analytical methods, are less frequent. Table 3 shows that, when the goal of the paper is related to proposing or studying a methodology (first column in Table 3 ), the percentage of pure quantitative papers is lower than in the rest of the cases. Regarding whether there is a tendency towards any methodology depending on the journal; Table 2 shows that the Journal on Engineering Design seems to focus more than the other journals on non-qualitative strategies of inquiry.

When quantitative methods are used, experiments are more frequent than quasi-experiments and non-experiments (14 out of the 17 quantitative studies present an experiment). We found 26 experimental studies, with 5 quasi-experiments (Saliminamin et al. 2019 ; Vegt et al. 2019 ; Sung et al. 2019 ; Self 2019 ; Santolaya et al. 2019 ) and 4 non-experiments (Selvefors et al. 2018 ; Morkos et al. 2019 ; Roesler et al. 2019 ; Piccolo et al. 2019 ).

The use of case studies is pervasive in qualitative research (more than half the studies that classified as qualitative base the research on a case study). Furthermore, many quantitative studies support results from case studies; for example, some analytical studies in which case studies are used as proof of concept of the proposed models (Chen et al. 2019b ; Zhang and Thomson 2019 ; Li et al. 2019a ).

Nevertheless, other qualitative methods, such as ethnography, hermeneutics, action research and phenomenological studies, are also used. The use of specific methods related to design is scarce (the discussion about this concern is dealt with in detail below). Ethnography is used in three cases (Roesler et al. 2019 ; Van der Linden et al. 2019a ; Comi et al. 2019 )—also the annotation as observation in the tables—and one more paper uses ethnography as the study focus (Wood and Mattson 2019 ). Hermeneutics is used by (McDonald and Michela 2019 ; Cooper 2019 ; Lloyd 2019 ; Luck 2019 ).

Action research is used by Pakkanen et al. ( 2019 ) to investigate, in combination with case studies, modular systems in industrial environments. The work of Bresciani ( 2019 ) could be considered an action research study with the goal of building a grounded theory evaluation technique for visual thinking. McKinnon and Sade ( 2019 ) align their work in the field of research through design using a set of gadgets to obtain information about environmental home good practices. Research through design is also used by Genç et al. ( 2018 ) to explore new materials and Tsai and Van Den Hoven ( 2018 ) to explore user experience. Hyysalo et al. ( 2019b ) and present the evaluation of a panel following the principles of research through design. Close to this method is that presented by Barati et al.( 2019 ), who complement their study with workshops where a group of students explores their proposals.

3.3 Data-collection methods

Results regarding RQ3 (data collection methods) are summarised in this section. Table 3 shows which main methods and techniques for collecting data are used in the different studies. The analysis of the sources of information is completed with a revision of the instruments used to collect data and with a discussion about the role of human input presented in the following sections. None of the data-collection methods identified seem to be dominant in the papers studied.

Technical documents of diverse nature are the main source of information used (Table 2 reports 23 out of the 68 papers analysed using technical documents). Interviewing is also frequent (22 times reported in Table 2 ). Expert and user opinions are both used as sources of information, but neither is a majority (22 and 20 papers, respectively, reported in Table 2 . Observation is mostly used in qualitative studies, where almost half use this technique. Concerning quantitative studies, apart from measurements, expert opinions appear as a frequent resource. This is because it is common to collect the opinions of experts in questionnaires or in evaluation templates that convert opinions into numeric values.

Verbalization is used in Martinec et al. ( 2019 ) and Gyory et al. ( 2019 ) for team work analysis and in (Khalaj and Pedgley 2019 ), where designers and users had to verbalize impressions.

Objects are collected as a data source in a relevant number of studies. Some are the results of students’ work as in Gralla et al. ( 2019 ); brainstorming outputs (Vegt et al. 2019 ); prototypes (Feijs and Toeters 2018 ; Barati et al. 2019 ), or commercial products (Roy and Warren 2019 ). Sketches are the type of object analysed in (Genç et al. 2018 ; Martinec et al. 2019 ; Gyory et al. 2019 ; Goucher-Lambert and Cagan 2019 ; Comi et al. 2019 ); while for (Li and Luximon 2018 ; Sung et al. 2019 ) sketches are the main concern of the research.

Questionnaires are less frequently used, and when this happens, they are designed ad-hoc for each study. Given the wide variety of topics and aims of the reviewed works, no standardised questionnaires have been found. Questionnaires, therefore, take different formats: Amazon Mechanical Turk is used once (Goucher-Lambert and Cagan 2019 ); a Likert scale tool evaluation (Graeff et al. 2019 ); binary and open questions (Pakkanen et al. 2019 ); ranking of preferences (Franceschini and Maisano 2019 ); or ad-hoc software tools (Li et al. 2019a ).

Interviews are frequently used as a source of information in qualitative and mixed strategies of inquiry. Interviews are associated with phenomenological studies (Li and Luximon 2018 ; Park-Lee and Person 2018 ; Selvefors et al. 2018 ) and also in ethnographic studies (Roesler et al. 2019 ; Van der Linden et al. 2019a ; Wood and Mattson 2019 ; Comi et al. 2019 ). The interviewed population can be a group of users of a given technology (Li and Luximon 2018 ) or a group of experts (Bresciani 2019 ).

Concerning the sample size used in the 24 papers whose research method has been classified as experimental, and taking into account that the sample may refer to studied objects or to participants/users, which, in turn, may be individuals or teams, the number of participants/users varies between 4, in Martinec et al. ( 2019 ), and 169, in Ozer and Cebeci ( 2019 ). The number of studied objects also varies from 6, in Mathias et al. ( 2019 ) to 256, in Li et al. ( 2019b ). In Santolaya et al. ( 2019 ) a methodology is experimentally tested in 2 case studies.

3.4 Instruments

Results regarding RQ4 (instruments used to collect data) are summarised in this section. Measurements refer both to metrics obtained with a physical device and to qualitative ratings obtained from human-based scores. In the first group, we can mention the metrics of energetic consumption (Selvefors et al. 2018 ; Santolaya et al. 2019 ), mass material (Santolaya et al. 2019 ), volumes of objects (Mathias et al. 2019 ), displacement of buttons (Valverde et al. 2019 ), online shopping user interaction data (Ozer and Cebeci 2019 ), or the timing of tasks in (Mathias et al. 2019 ). In the second group, we can cite (Saliminamin et al. 2019 ; Gyory et al. 2019 ), which score the quality of design proposals, and (Franceschini and Maisano 2019 ), who use design preferences as the input for an analytical model.

Simulations and/or software developments of algorithms take on an important role in several papers. Belkadi et al. ( 2019 ) present a software tool; Chen et al. ( 2019a ), Feijs and Toeters ( 2018 ), Mathias et al. ( 2019 ) and Takahashi et al. ( 2018 ) present or test software tools for different goals, such as analysing Lego buildings, and generating fashion patterns for projecting requirements into design parameters. Li et al. ( 2019a ) focus on modelling knowledge; Piccolo et al. ( 2019 ) use analysis and visualization tools to present results; while Ozer and Cebeci ( 2019 ) and Saravanan and Jerald ( 2019 ) use machine learning techniques such as neural networks and clustering. De Lessio et al. ( 2019 ) present a software tool to support planning and Yang et al. ( 2019 ) to support manufacturing. Boussuge et al. ( 2019 ) propose using ontologies to capture high-level modelling and idealisation decisions, characterising the simulations of CAE models from CAD assemblies. Other papers related to ontologies use software to model them (Cheong and Butscher 2019 ; Hagedorn et al. 2019 ; Wang et al. 2019 ).

Workshops are frequently used for evaluating results and sharing experiences by a group of experts with discussions (Van der Linden et al. 2019a , b ; McKinnon and Sade 2019 ; Self 2019 ; Wlazlak et al. 2019 ). In (Genç et al. 2018 ; Martinec et al. 2019 ), the workshops become designing activities in the research-through-design methodology. In Takahashi et al. ( 2018 ), workshops are used to observe users while they interact with a system and, in Pakkanen et al. ( 2019 ), to collect information from experts. In Garcia et al. ( 2019 ), workshops are meetings with stakeholders.

The opinions of stakeholders can be the core of the research study (Self 2019 ) or they can be used as part of usability tests (Takahashi et al. 2018 ). Most often, questionnaires and interviews are performed with users of a product (Selvefors et al. 2018 ; Roesler et al. 2019 ; Hanrahan et al. 2019 ; Ozer and Cebeci 2019 ); by active participants of the process under analysis, such as professionals in companies (Reimlinger et al. 2019 ; Wlazlak et al. 2019 ); or by students that are required to do a project (Vegt et al. 2019 ; Li et al. 2019a ; Abi Akle et al. 2019 ; Graeff et al. 2019 ). The experts that participate in questionnaires or interviews are designers, architects, engineers (Li and Luximon 2018 ; Park-Lee and Person 2018 ; Pakkanen et al. 2019 ), or academic staff evaluating results (Morkos et al. 2019 ; Sung et al. 2019 ; McKinnon and Sade 2019 ). In interviews occurring in ethnographic studies, the subjects providing information could be considered the topic of analysis (Wood and Mattson 2019 ), but at the same time, they could be experts (Comi et al. 2019 ).

4 Discussion

4.1 variety of aims and approaches.

The principal finding of our research is that there is a very high diversity in the works we have analysed in the journals related to engineering design. This variety affects the aims and scopes of the research works, the methods, and the data sources. Table 4 shows that variety affects the papers in the four journals analysed with only minor differences among them. Thus, DS (Design Studies) and RED (Research in Engineering Design) seem to focus more on methodological aspects, while IJD (International Journal of Design) and JED (Journal of Engineering Design) focus more on delving into particular aspects of the design process or on products, but at most 7 papers out of the 17 falls into one of the categories. According to the results, DS and IJD journals attract more papers with a qualitative approach (only 2 papers in each journal are purely quantitative), while most of the papers from JED and RED follow a quantitative or analytical approach (only 3 and 7 papers, respectively, are purely qualitative). However, we have found papers with both approaches in all the journals. RED uses less self-reported data (interviews, questionnaires or workshops), while DS uses this source of data the most, but in both journals there are exceptions, such as the works of Mathias et al. ( 2019 ) in DS or Garcia et al. ( 2019 ) in RED.

Despite this broad spectrum of papers, we found a clear interest in methodologies and the in-depth analysis of a given aspect of the whole process of designing generally applied to a particular case study. The interest in both topics is justified by the nature of the design and the youth of the discipline. As a process of searching for optimum solutions, design is clearly related to methodological concerns. As a young discipline, the space for contributing to the different tasks of the whole design process is huge. The analysis of the process of engineering design has evolved from being considered from a purely technical perspective to being studied as a socio-technical process. From a technical point of view, (Beitz et al. 1996 ) distinguished between conceptual design and embodied design for identifying a list of tasks that contribute to facing problems of engineering design in an effective and systematic way. From a socio-technical perspective, different authors have pointed out that the design process is influenced by aspects related to teamwork capabilities (Dorst 2004 ), the inclusion of participants (Van der Bijl-Brouwer and Dorst 2017 ) or by the institutional complexity (Reich and Subrahmanian 2020 ). Our study shows that there is space for research works that focus on both perspectives of analysis, being found works that are closely related to tasks that affect conceptual design (Martinec et al. 2019 ; Benavides and Lara-Rapp 2019 ; Self 2019 ), embodied design (Petreca et al. 2019 ) and also to social aspects of the design process (Piccolo et al. 2019 ).

It has been observed that there are a relatively low number of papers proposing recommendations, guidelines, frameworks, and taxonomies. We understand how difficult it is generalizing and classifying a discipline with multiple tasks, agents, approaches and sub-domains. Nevertheless, generating these types of representations of knowledge could be a substrate for the growth of the discipline. Design is a context-specific endeavour, but trying to generalize results so that other authors could reuse the generated knowledge in other domains would be positive for the growth of the discipline. The selected papers include product development and engineering design, which are two different areas, albeit overlapping. Recommendations and guidelines are always useful for the practice of engineering design, but more importantly, classifying concepts and types of activities with frameworks and taxonomies is an essential process in the building of knowledge in any research area. The variety of aims and approaches is probably the reason for this deficit, but research in engineering design would benefit from works analysing the many methodologies proposed from a meta level that permits obtaining general concepts that are domain-independent and universally applicable.

Results presented in Table 2 and summarised in Table 3 could be used to derive patterns or preferred styles in research design. Papers using analytical approaches mainly use case studies to validate the proposed models and they use simulations to compare results with expectations. Here, the case studies are used as proof of concept of the proposed models. They do not consider human input as a main feature of analysis. The ones related to methodological concerns are the papers focusing on axiomatic design and the ones relating to specific aspects or to frameworks are the ones related to ontologies. Most papers with quantitative approaches use experimental setups in which they compare different configurations of a given problem. The means to collect numerical data highly depend on the type of work, with no outstanding method or instrument. This approach is mainly used when the goal is to study a given aspect of design, which is coherent with the fact that experiments are meant to measure variables that can be isolated, and therefore these studies need to focus on specific features of the design process. Like analytical papers, qualitative approaches are mainly based on case studies. The main difference is related to the nature of these case studies. In qualitative approaches, the case studies aim at gaining insight into the complexity of the studied design processes from the point of view of the participants. In consequence, the preferred data collection methods are observations and interviews and/or workshops, to collect data from users and experts. They use rich data sources (audio, photography, video or software tools) to make observations rigorously. Qualitative approaches are the most used methods, independently of the aim of the paper, but they are dominant for proposing frameworks of analysis or deriving guidelines and recommendations, probably because the active interpretation of experts is a must for these concerns. Papers using mixed methods triangulate the information obtained in quantitative experiments with information obtained with qualitative methods. Therefore, their pattern is closer to one of the papers using quantitative methods than to the ones using qualitative methods.

The application of one approach or another should respond to what Subrahmanian et al. ( 2020 ) call the different models of designing. When the artifact or the process is clear, analytical, and quantitative methods, closer to approaches followed in natural science can be applied. When people, culture, society, and politics must be taken into consideration, the use of analytical and quantitative methods is not appropriate. When individual designers play a role, and, especially, when social aspects and context must be taken into consideration, design processes become more complex and dynamic, involving aspects that are better studied by qualitative approaches that are able to capture the complexity of the object of study and the participants' perspectives.

4.2 Implications for the research in the engineering design community

As mentioned in the introduction, one of the objectives of this paper was to provide suggestions about the course contents that doctoral studies in the domain of engineering design must carry out. The first implication of our analysis relates to the type of research methodologies that students must be introduced to. According to the analysed papers, it seems essential that future researchers receive training in both qualitative and quantitative methods. The analysis shows that qualitative research is very common and that rich sources of data, such as observations or users and experts opinions collected through interviews are frequent. Furthermore, pure qualitative research approaches, like ethnography and phenomenology are commonly found. Nevertheless, experimental approaches should also have a relevant role in the student curricula because it is frequently used as well. We understand that this qualitative-quantitative duality responds to the nature of engineering design, a complex field that requires both technical background and the consideration of behavioural and social aspects related to design.

A second implication has to do with the instruments and data collection methods that researchers on engineering design must get familiar with. Research studies in this domain could require accessing real design scenarios that are authentic field studies rather than controlled lab studies. This is a relevant divergence with respect to other research domains that permit isolating variables and participants. There are implications for the instruments used for collecting data, with the need of considering techniques that permit collecting information in real settings and during longer periods of time. but also, that human fact is a relevant variable that affects both design teams managements, communication with users and social aspects. This fact justifies the use of technical reports, questionnaires, and observation as the main sources of information in these studies.

It must be noted that publishing in a journal should not be an end in itself, and the real value of a paper does not rely on the journal in which it is published but on its contribution to the growth of the discipline (Bladek 2014 ). However, there is a universal tendency to identify research quality and impact with these publications, and students that pursue a research career usually need to accomplish certain goals related to publishing. For this reason, we think that doctoral students in engineering design can find this work useful, as it provides an overview and pointers to different types of research work published in four top-quality journals in the field, and this may give them tips on the kind of knowledge they need to acquire to have their work published in these journals or similar ones.

4.3 Relation to other surveys

Probably due to the youth of engineering design as a research discipline, the number of papers devoted to literature reviews in these fields is still sparse. From the few reviews found, most refer to particular aspects of engineering design: such as inspiration and fixation (Crilly 2019 ); sustainability (Coskun et al. 2015 ); user value (Boztepe 2007 ); Alzheimer and play experience (Anderiesen et al. 2015 ); performance in industrial design(Candi and Gemser 2010 ); relation between creativity, functionality, and aesthetics (Han et al. 2021 ); fuzzy front-ends for product development (Park et al. 2021 ); surrogate models and computational complexity (Alizadeh et al. 2020 ); smart design (Pessôa and Becker 2020 ); design and poverty (Jagtap 2019 ); mass customization (Ferguson et al. 2014 ); product stigma (Schröppel et al. 2021 ); uncertainty (Han et al. 2020 ); decision-making methods (Renzi et al. 2017 ); modular product design (Bonvoisin et al. 2016 ); or product-service systems (Vasantha et al. 2012 ).

More interesting, for their similarity with respect to the present study, are the works presented by Tempczyk ( 1986 ) and Cantamessa ( 2003 ), both presenting reviews or surveys about research and studies on engineering design. These two works and the one presented in this paper differ in their sources of information. Tempczyk ( 1986 ) made a survey by sending questionnaires to academic staff concerning research subjects and methods; Cantamessa ( 2003 ) made a review of the proceedings of two editions of the conference on engineering design. There is a temporal distance of 17 years between the work of Tempczyk ( 1986 ) and the one of Cantamessa ( 2003 ) and 18 years between the work of Cantamessa ( 2003 ) and the present study, but we must highlight the fact that the three studies report methodologies as one of the main topics of research. Computer-aided products are reported by Tempczyk ( 1986 ) as a relevant topic, and Cantamessa ( 2003 ) also refers to software tools as a recurrent topic, while we also identified a category named simulation which included software tools and algorithms. The three works also report a high variety of approaches and themes. The main difference between these studies and the present one is that Tempczyk ( 1986 ) reports on training as an important concern for researchers and Cantamessa ( 2003 ) observes different streams of research, loosely coupled with an excess of referencing to previous works. As regards references to training concerns, we did not find any paper related to training, probably because, nowadays, there are journals specifically devoted to learning in the domain of engineering and design. As regards the criticism of Cantamessa ( 2003 ) concerning the notable amount of self-references in the analysed papers, we did not observe such a circumstance in the journal papers we have reviewed. On the contrary, our review has found that the papers reviewed contain complete state-of-the-art sections in which other research groups are referenced and other studies are discussed. This finding partially contradicts what Cantamessa ( 2003 ) found in his review. We think that the nature of the sources of data in his review, based on proceedings which are shorter could have influenced these divergent results. Our study may point to a more mature stage of research that builds on the knowledge already offered in the community. This finding may be based on the fact we are working on journal papers that offer more mature results.

4.4 Limitations

The systematic literature review presented in this paper covers a recent period of time spanning one year of publications. The sample is representative of recent research in engineering design, but it does not provide information about tendencies in the field. For example, we have observed a relevant number of quantitative studies in comparison to qualitative ones, but we cannot say if this is a tendency. Future work would be required to compare our results with those of a longitudinal study covering a larger period of years. We expect that our work can be considered as the first step in this longer-term study that could provide useful information about the evolution of research into the young discipline of engineering design.

By selecting Blessing and Chakrabarti ( 2009 ) as a framework to categorize research papers, we did not pay attention to the important concern of the success of the research which could be a critical point for connecting the study aim, with the approach, research method, etc. Reich and Subrahmanian ( 2021 ) show that it is possible to use the PSI framework (Problem, Social and Institutional space) to describe what researchers and designers did in case studies to analyse the matching of methods, aims and approaches with the success of the projects. In spite of our work being merely descriptive of the aims, methods and techniques used by authors, we offer a corpus of categorised research papers for analysing in future works on whether the research design is appropriate for its goals.

The analysis of the sample of journal papers selected has permitted us to build a consistent set of categories for classifying research works in engineering design. We consider this sample comprehensive, based on a saturation analysis carried out on the sample, that showed that all the categories used in the analysis could be identified with 69% of the papers that were actually used in the analysis. Nevertheless, while selecting 68 papers from only four journals, we could have discarded other works that could include other alternative approaches also valid for research in engineering design. Moreover, the choice of a single year-window is another limitation of this study, as it does not enable us to provide a full vision of the field and its evolution. Nevertheless, we think that the classification presented in this paper could be the basis for subsequent studies, which should consider a broader timeframe, and therefore, a larger selection of papers across several years. Other approaches for selecting the analysed papers like sampling at the same rate in all the journals could also have led to representative results.

5 Conclusions

In this paper, we have presented a systematic review of recent literature on research methods and instruments used in a one-year period of research papers in the field of engineering design. By taking this approach, we offer a "fixed image" of recent research in the area and point to some gaps and challenges in the field.

The review shows that there is no single methodological approach accepted as the standard in the field; and that there is a large variety of goals, approaches, data collection methods and instruments to collect them. In spite of this variety, we have observed a certain preference towards qualitative methods, which can be justified by the increasing consideration of engineering design as a complex process affecting humans and their contexts.

We think that this paper contributes to research in engineering design by providing initial evidence for researchers about the kind of work that are expected by high-impact scientific journals in this domain. Additionally, academics can find in this paper a list of topics (methodologies, data-collection procedures, instruments, etc.…) that must be part of the programme of courses on research in engineering design.

6 Appendix: Coding scheme: categories and examples

The tables included in this Appendix have aim to present the knowledge generated in this paper in the form of a coding scheme, that can be used as an instrument to describe the taxonomy of research aims (Table 5 ), approaches (Table 6 ), data collection techniques (Table 7 ), and instruments (Table 8 ) in engineering design.

Data Availability

All data generated or analysed during this study are included in this published article [and its supplementary information files].

Abi Akle A, Yannou B, Minel S (2019) Information visualisation for efficient knowledge discovery and informed decision in design by shopping. J Eng Des 30:227–253. https://doi.org/10.1080/09544828.2019.1623383

Article   Google Scholar  

Adrion WR (1993) Research methodology in software engineering. In: Summary of the Dagstuhl workshop on future directions in software engineering” Ed. Tichy, Habermann, and Prechelt, ACM software engineering notes, SIGSoft, pp 36–37

Aktas BM, Mäkelä M (2019) Negotiation between the maker and material: observations on material interactions in felting studio. Int J Des 13:55–67

Google Scholar  

Alizadeh R, Allen JK, Mistree F (2020) Managing computational complexity using surrogate models: a critical review. Res Eng Des 31:275–298. https://doi.org/10.1007/s00163-020-00336-7

Anderiesen H, Scherder E, Goossens R et al (2015) Play experiences for people with Alzheimer’s disease. Int J Des 9:155–165

Atkinson P (1988) Ethnomethodology: A Critical Review. Annu Rev Sociol 14:441–465. https://doi.org/10.1146/annurev.so.14.080188.002301

Barati B, Karana E, Hekkert P (2019) Prototyping materials experience: towards a shared understanding of underdeveloped smart material composites. Int J Des 13:21–38

Behera AK, McKay A, Earl CF et al (2019) Sharing design definitions across product life cycles. Res Eng Des 30:339–361. https://doi.org/10.1007/s00163-018-00306-0

Beitz W, Pahl G, Grote K (1996) MRS Bull 21:71.  https://doi.org/10.1557/S0883769400035776

Belkadi F, Le DuigouDall’Olio JL et al (2019) Knowledge-based platform for traceability and simulation monitoring applied to design of experiments process: an open source architecture. J Eng Des 30:311–335. https://doi.org/10.1080/09544828.2019.1642463

Benavides EM, Lara-Rapp O (2019) Ideal output for a robust conceptual design process. J Eng Des 30:103–154. https://doi.org/10.1080/09544828.2019.1598552

Bergstrom JR, Schall A (2014) Eye tracking in user experience design. Elsevier, Amsterdam

Bladek M (2014) DORA: San Francisco declaration on research assessment (May 2013). Coll Res Libr News 75:191–196

Blessing LTM, Chakrabarti A (2009) DRM: a design reseach methodology. Springer, Berlin

Book   Google Scholar  

Bogle D (2018) 100 years of the PhD in the UK. In: Proceedings of vitae researcher development international conference 2018, p 12

Bonvoisin J, Halstenberg F, Buchert T, Stark R (2016) A systematic literature review on modular product design. J Eng Des 27:488–514. https://doi.org/10.1080/09544828.2016.1166482

Boussuge F, Tierney CM, Vilmart H et al (2019) Capturing simulation intent in an ontology: CAD and CAE integration application. J Eng Des 30:688–725. https://doi.org/10.1080/09544828.2019.1630806

Boztepe S (2007) User value: competing theories and models. Int J Des 1:55–63

Bresciani S (2019) Visual design thinking: a collaborative dimensions framework to profile visualisations. Des Stud 63:92–124. https://doi.org/10.1016/j.destud.2019.04.001

Brewer MB, Crano WD (2014) Research design and issues of validity. In: Reis HT, Judd CM (eds) Handbook of research methods in social and personality psychology, 2nd edn. Cambridge University Press, New York, NY, USA, pp 11–26

Candi M, Gemser G (2010) An agenda for research on the relationships between industrial design and performance. Int J Des 4:67–77

Cantamessa M (2003) An empirical perspective upon design research. J Eng Des 14:1–15. https://doi.org/10.1080/0954482031000078126

Chen B, Hu J, Chen W (2019a) DRE-based semi-automation of the axiomatic design transformation: from the functional requirement to the design parameter. J Eng Des 30:255–287. https://doi.org/10.1080/09544828.2019.1627296

Chen R, Liu Y, Fan H et al (2019b) An integrated approach for automated physical architecture generation and multi-criteria evaluation for complex product design. J Eng Des 30:63–101. https://doi.org/10.1080/09544828.2018.1563287

Cheong H, Butscher A (2019) Physics-based simulation ontology: an ontology to support modelling and reuse of data for physics-based simulation. J Eng Des 30:655–687. https://doi.org/10.1080/09544828.2019.1644301

Clark JS, Porath S, Thiele J, Jobe M (2020) Action research. New Prairie Press, Paris

Comi A, Jaradat S, Whyte J (2019) Constructing shared professional vision in design work: the role of visual objects and their material mediation. Des Stud 64:90–123. https://doi.org/10.1016/j.destud.2019.06.003

Cooper R (2019) Design research—its 50-year transformation. Des Stud 65:6–17. https://doi.org/10.1016/j.destud.2019.10.002

Coskun A, Zimmerman J, Erbug C (2015) Promoting sustainability through behavior change: a review. Des Stud 41:183–204. https://doi.org/10.1016/j.destud.2015.08.008

Cranz G (2016) Ethnography for designers. Routledge, London

Creswell JW (2009) Research design: qualitative, quantitative and mixed approaches, 3rd edn

Crilly N (2019) Creativity and fixation in the real world: a literature review of case study research. Des Stud 64:154–168. https://doi.org/10.1016/j.destud.2019.07.002

Cuff D (1992) Architecture: the story of practice. MIT Press, London

Daalhuizen J, Timmer R, Van Der Welie M, Gardien P (2019) An architecture of design doing: a framework for capturing the ever-evolving practice of design to drive organizational learning. Int J Des 13:37–52

De Leeuw ED (2008) Choosing the method of data collection

De Lessio MP, Wynn DC, Clarkson PJ (2019) Modelling the planning system in design and development. Res Eng Des 30:227–249. https://doi.org/10.1007/s00163-017-0272-5

Diggle PJ, Chetwynd AG, Chetwynd A (2011) Statistics and scientific method: an introduction for students and researchers. Oxford University Press, Oxford

Book   MATH   Google Scholar  

Dorst K (2004) On the problem of design problems—problem solving and design expertise. J Des Res 4:185–196. https://doi.org/10.1504/JDR.2004.009841

Eikeland O (2006) The validity of action research—validity in action research. In: Aagaard Nielsen K, Svensson L (eds) Action research and interactive research. Shaker Publishing, Maastricht, pp 193–240

Feijs L, Toeters M (2018) Cellular automata-based generative design of Pied-de-poule patterns using emergent behavior: case study of how fashion pieces can help to understand modern complexity. Int J Des 12:127–144

Ferguson SM, Olewnik AT, Cormier P (2014) A review of mass customization across marketing, engineering and distribution domains toward development of a process framework. Res Eng Des 25:11–30. https://doi.org/10.1007/s00163-013-0162-4

Fink AS (2000) The role of the researcher in the qualitative research process. A potential barrier to archiving qualitative data. In: Forum Qualitative Sozialforschung/Forum: Qualitative Social Research

Franceschini F, Maisano D (2019) Design decisions: concordance of designers and effects of the Arrow’s theorem on the collective preference ranking. Res Eng Des 30:425–434. https://doi.org/10.1007/s00163-019-00313-9

Garcia JJ, Pettersen SS, Rehn CF et al (2019) Overspecified vessel design solutions in multi-stakeholder design problems. Res Eng Des 30:473–487. https://doi.org/10.1007/s00163-019-00319-3

Genç Ç, Buruk OT, Yılmaz Sİ et al (2018) Exploring computational materials for fashion: recommendations for designing fashionable wearables. Int J Des 12:1–19

Glass RL (1995) A structure-based critique of contemporary computing research. J Syst Softw 28:3–7. https://doi.org/10.1016/0164-1212(94)00077-Z

Goodwin C (2000) Practices of seeing visual analysis: an ethnomethodological approach. SAGE Publications Ltd, London

Goucher-Lambert K, Cagan J (2019) Crowdsourcing inspiration: using crowd generated inspirational stimuli to support designer ideation. Des Stud 61:1–29. https://doi.org/10.1016/j.destud.2019.01.001

Graeff E, Maranzana N, Aoussat A (2019) Biomimetics, where are the biologists? J Eng Des 30:289–310. https://doi.org/10.1080/09544828.2019.1642462

Gralla EL, Herrmann JW, Morency M (2019) Design problem decomposition: an empirical study of small teams of facility designers. Res Eng Des 30:161–185. https://doi.org/10.1007/s00163-018-0300-0

Gyory JT, Cagan J, Kotovsky K (2019) Are you better off alone? Mitigating the underperformance of engineering teams during conceptual design through adaptive process management. Res Eng Des 30:85–102. https://doi.org/10.1007/s00163-018-00303-3

Hagedorn TJ, Smith B, Krishnamurty S, Grosse I (2019) Interoperability of disparate engineering domain ontologies using basic formal ontology. J Eng Des 30:625–654. https://doi.org/10.1080/09544828.2019.1630805

Han J, Forbes H, Schaefer D (2021) An exploration of how creativity, functionality, and aesthetics are related in design. Res Eng Des 32:289–307. https://doi.org/10.1007/s00163-021-00366-9

Han X, Li R, Wang J et al (2020) A systematic literature review of product platform design under uncertainty. J Eng Des 31:266–296. https://doi.org/10.1080/09544828.2019.1699036

Hanrahan BV, Yuan CW, Rosson MB et al (2019) Materializing interactions with paper prototyping: a case study of designing social, collaborative systems with older adults. Des Stud 64:1–26. https://doi.org/10.1016/j.destud.2019.06.002

Hatchuel A (2001) Towards design theory and expandable rationality: the unfinished program of Herbert Simon. J Manag Gov 5:260–273. https://doi.org/10.1023/A:1014044305704

Herr CM (2015) Action research as a research method in architecture and design. In: Proceedings of the 59th annual meeting of the ISSS-2015 Berlin, Germany

Hiebl MRW (2021) Sample selection in systematic literature reviews of management research. Organ Res Methods. https://doi.org/10.1177/1094428120986851

Hobye M, Ranten MF (2019) Behavioral complexity as a computational material strategy. Int J Des 13:39–53

Hyysalo S, Hyysalo V, Hakkarainen L (2019a) The work of democratized design in setting-up a hosted citizen-designer community. Int J Des 13:69–82

Hyysalo S, Marttila T, Perikangas S, Auvinen K (2019b) Codesign for transitions governance: a mid-range pathway creation toolset for accelerating sociotechnical change. Des Stud 63:181–203. https://doi.org/10.1016/j.destud.2019.05.002

Jagtap S (2019) Design and poverty: a review of contexts, roles of poor people, and methods. Res Eng Des 30:41–62. https://doi.org/10.1007/s00163-018-0294-7

Joost G, Bredies K, Christensen M et al (2016) Design as research: Positions, arguments, perspectives. Birkhäuser, Basel

Jørgensen U (2001) Grounded theory: methodology and theory construction. Int Encycl Soc Behav Sci 1:6396–6399

Kennedy-Clark S (2013) Research by design: design-based research and the higher degree research student. J Learn Des 6:26–32

Khalaj J, Pedgley O (2019) A semantic discontinuity detection (SDD) method for comparing designers’ product expressions with users’ product impressions. Des Stud 62:36–67. https://doi.org/10.1016/j.destud.2019.02.002

King N, Horrocks C, Brooks J (2019) Interviews in qualitative research, 2nd edn. Sage, London

Kitchenham B, Pearl Brereton O, Budgen D et al (2009) Systematic literature reviews in software engineering—a systematic literature review. Inf Softw Technol 51:7–15. https://doi.org/10.1016/j.infsof.2008.09.009

Koskinen I, Zimmerman J, Binder T et al (2011) Design research through practice: from the lab, field, and showroom. Elsevier, Amsterdam

Kothari CR (2004) Research methodology: methods and techniques. New Age International, New Delhi

Lapan SD, Quartaroli MT, Riemer FJ (eds) (2012) Qualitative research: an introduction to methods and designs. Jossey-Bass/Wiley, New York

Li Q, Luximon Y (2018) Understanding older adults’ post-adoption usage behavior and perceptions of mobile technology. Int J Des 12:93–110

Li Y, Roy U, Saltz JS (2019a) Towards an integrated process model for new product development with data-driven features (NPD3). Res Eng Des 30:271–289. https://doi.org/10.1007/s00163-019-00308-6

Li Y, Shieh M-D, Yang C-C (2019b) A posterior preference articulation approach to Kansei engineering system for product form design. Res Eng Des 30:3–19. https://doi.org/10.1007/s00163-018-0297-4

Lloyd P (2019) You make it and you try it out: Seeds of design discipline futures. Des Stud 65:167–181. https://doi.org/10.1016/j.destud.2019.10.008

Luck R (2019) Design research, architectural research, architectural design research: an argument on disciplinarity and identity. Des Stud 65:152–166. https://doi.org/10.1016/j.destud.2019.11.001

MacQueen KM, Guest G (2008) An introduction to team-based qualitative research. In: Guest G, MacQueen KM (eds) Handbook for team-based qualitative research. Altamira Press, Lanham, pp 3–19

Martinec T, Škec S, Horvat N, Štorga M (2019) A state-transition model of team conceptual design activity. Res Eng Des 30:103–132. https://doi.org/10.1007/s00163-018-00305-1

Mathias D, Snider C, Hicks B, Ranscombe C (2019) Accelerating product prototyping through hybrid methods: coupling 3D printing and LEGO. Des Stud 62:68–99. https://doi.org/10.1016/j.destud.2019.04.003

McDonald JK, Michela E (2019) The design critique and the moral goods of studio pedagogy. Des Stud 62:1–35. https://doi.org/10.1016/j.destud.2019.02.001

McKinnon H, Sade G (2019) Exploring the home environment: fusing rubbish and design to encourage participant agency and self-reflection. Des Stud 63:155–180. https://doi.org/10.1016/j.destud.2019.05.001

Menold J, Simpson TW, Jablokow K (2019) The prototype for X framework: exploring the effects of a structured prototyping framework on functional prototypes. Res Eng Des 30:187–201. https://doi.org/10.1007/s00163-018-0289-4

Miles MB, Huberman AM, Saldaña J (2020) Qualitative data analysis: a methods sourcebook, 4th edn. SAGE Publications Inc., London

Morkos B, Joshi S, Summers JD (2019) Investigating the impact of requirements elicitation and evolution on course performance in a pre-capstone design course. J Eng Des 30:155–179

Motta-Filho MA (2021) Brand experience manual: bridging the gap between brand strategy and customer experience. Rev Manag Sci 15:1173–1204

Ohnemus KR, Biers DW (1993) Retrospective versus concurrent thinking-out-loud in usability testing. In: Proceedings of the human factors and ergonomics society annual meeting. SAGE Publications Sage CA, Los Angeles, pp 1127–1131

Ozer M, Cebeci U (2019) Affective design using big data within the context of online shopping. J Eng Des 30:368–384. https://doi.org/10.1080/09544828.2019.1656803

Pakkanen J, Juuti T, Lehtonen T (2019) Identifying and addressing challenges in the engineering design of modular systems—case studies in the manufacturing industry. J Eng Des 30:32–61. https://doi.org/10.1080/09544828.2018.1552779

Paluck EL, Cialdini RB (2014) Field research methods. In: Reis HT, Judd CM (eds) Handbook of research methods in social and personality psychology, 2nd edn. Cambridge University Press, New York, NY, USA, pp 81–97

Park-Lee S, Person O (2018) Briefng beyond documentation: an interview study on industrial design consulting practices in Finland. Int J Des 12:73–91

Park D, Han J, Childs PRN (2021) 266 Fuzzy front-end studies: current state and future directions for new product development. Res Eng Des 32:377–409. https://doi.org/10.1007/s00163-021-00365-w

Pedgley O, Şener B, Lilley D, Bridgens B (2018) Embracing material surface imperfections in product design. Int J Des 12:21–33

Pérez-Gómez A (1999) Hermeneutics as discourse in design. Des Issues 15:71–79

Pessôa MVP, Becker JMJ (2020) Smart design engineering: a literature review of the impact of the 4th industrial revolution on product design and development. Res Eng Des 31:175–195

Petreca B, Saito C, Baurley S et al (2019) Radically relational tools: a design framework to explore materials through embodied processes. Int J Des 13:7–20

Piccolo SA, Maier AM, Lehmann S, McMahon CA (2019) Iterations as the result of social and technical factors: empirical evidence from a large-scale design project. Res Eng Des 30:251–270. https://doi.org/10.1007/s00163-018-0301-z

Radhakrishna RB (2007) Tips for developing and testing questionnaires/instruments. J Ext 45:1TOT2

Randolph MF (2003) Science and empiricism in pile foundation design. Géotechnique 53:847–875

Rapley T, Rees G (2018) Collecting documents as data. In: Flick U (ed) The SAGE handbook of qualitative data collection. Sage, London, pp 378–391

Chapter   Google Scholar  

Redström J (2017) Making design theory. MIT Press, London

Reich Y, Subrahmanian E (2021) Mapping and enhancing design studies with psI meta-theoretic design framework. Proc Des Soc 1:2007–2016. https://doi.org/10.1017/pds.2021.462

Reich Y, Subrahmanian E (2020) The PSI framework and theory of design. IEEE Trans Eng Manag. https://doi.org/10.1109/TEM.2020.2973238

Reimlinger B, Lohmeyer Q, Moryson R, Meboldt M (2019) A comparison of how novice and experienced design engineers benefit from design guidelines. Des Stud 63:204–223. https://doi.org/10.1016/j.destud.2019.04.004

Renzi C, Leali F, Di Angelo L (2017) A review on decision-making methods in engineering design for the automotive industry. J Eng Des 28:118–143. https://doi.org/10.1080/09544828.2016.1274720

Roesler A, Grigg EB, Martin LD et al (2019) Practice-centered design of an anesthesia medication template to reduce medication handling errors in the operating room. Int J Des 13:53–68

Roy R, Warren JP (2019) Card-based design tools: a review and analysis of 155 card decks for designers and designing. Des Stud 63:125–154. https://doi.org/10.1016/j.destud.2019.04.002

Saldaña J (2021) The coding manual for qualitative researchers, 4th edn. SAGE Publications Ltd, Thousand Oaks

Saliminamin S, Becattini N, Cascini G (2019) Sources of creativity stimulation for designing the next generation of technical systems: correlations with R&D designers’ performance. Res Eng Des 30:133–153. https://doi.org/10.1007/s00163-018-0299-2

Santolaya JL, Lacasa E, Biedermann A, Muñoz N (2019) A practical methodology to project the design of more sustainable products in the production stage. Res Eng Des 30:539–558. https://doi.org/10.1007/s00163-019-00320-w

Saravanan A, Jerald J (2019) Ontological model-based optimal determination of geometric tolerances in an assembly using the hybridised neural network and genetic algorithm. J Eng Des 30:180–198. https://doi.org/10.1080/09544828.2019.1605585

Schröppel T, Miehling J, Wartzack S (2021) The role of product development in the battle against product-related stigma—a literature review. J Eng Des 32:247–270. https://doi.org/10.1080/09544828.2021.1879031

Self JA (2019) Communication through design sketches: implications for stakeholder interpretation during concept design. Des Stud 63:1–36. https://doi.org/10.1016/j.destud.2019.02.003

Selvefors A, Marx C, Karlsson MAIC, Rahe U (2018) (How) can appliances be designed to support less energy-intensive use? Insights from a field study on kitchen appliances. Int J Des 12:35–55

Simon HA (1996) The science of design: creating the artificial

Solomon M (2007) Social empiricism. MIT Press, Cambridge

Stigliano A (1989) Hermeneutical practice. Saybrook Rev 7:47–67

Stringer ET (2008) Action research in education. Pearson Prentice Hall, Upper Saddle River

Subrahmanian E, Reich Y, Krishnan S (2020) We are not users: dialogues, diversity, and design. MIT Press, Cambridge

Sung E, Kelley TR, Han J (2019) Influence of sketching instruction on elementary students’ design cognition: a study of three sketching approaches. J Eng Des 30:199–226. https://doi.org/10.1080/09544828.2019.1617413

Swann C (2002) Action research and the practice of design. Des Issues 18:49–61

Tahera K, Wynn DC, Earl C, Eckert CM (2019) Testing in the incremental design and development of complex products. Res Eng Des 30:291–316. https://doi.org/10.1007/s00163-018-0295-6

Takahashi I, Oki M, Bourreau B et al (2018) An empathic design approach to an augmented gymnasium in a special needs school setting. Int J Des 12:111–125

Tempczyk H (1986) A survey of research and studies on design. Des Stud 7:199–215. https://doi.org/10.1016/0142-694X(86)90037-2

Tenopir C, King DW (2014) The growth of journals publishing. In: The future of the academic journal. Elsevier, Amsterdam, pp 159–178

Thiese MS (2014) Observational and interventional study design types; an overview. Biochem Medica 24:199–210

Tsai WC, Van Den Hoven E (2018) Memory probes: exploring retrospective user experience through traces of use on cherished objects. Int J Des 12:57–72

Valverde N, Ribeiro AMR, Henriques E, Fontul M (2019) An engineering perspective on the quality of the automotive push-buttons’ haptic feedback in optimal and suboptimal interactions. J Eng Des 30:336–367. https://doi.org/10.1080/09544828.2019.1656802

Van der Bijl-Brouwer M, Dorst K (2017) Advancing the strategic impact of human-centred design. Des Stud 53:1–23. https://doi.org/10.1016/j.destud.2017.06.003

Van der Linden V, Dong H, Heylighen A (2019a) Populating architectural design: introducing scenario-based design in residential care projects. Int J Des 13:21–36

Van der Linden V, Dong H, Heylighen A (2019b) Tracing architects’ fragile knowing about users in the socio-material environment of design practice. Des Stud 63:65–91. https://doi.org/10.1016/j.destud.2019.02.004

Van Kuijk J, Daalhuizen J, Christiaans H (2019) Drivers of usability in product design practice: induction of a framework through a case study of three product development projects. Des Stud 60:139–179. https://doi.org/10.1016/j.destud.2018.06.002

Vasantha GVA, Roy R, Lelah A, Brissaud D (2012) A review of product–service systems design methodologies. J Eng Des 23:635–659. https://doi.org/10.1080/09544828.2011.639712

Vaughan L (2017) Practice-based design research. Bloomsbury Publishing, London

Vegt N, Visch V, Vermeeren A et al (2019) Balancing game rules for improving creative output of group brainstorms. Int J Des 13:1–19

Wang R, Nellippallil AB, Wang G et al (2019) Ontology-based uncertainty management approach in designing of robust decision workflows. J Eng Des 30:726–757. https://doi.org/10.1080/09544828.2019.1668918

Wasson C (2000) Ethnography in the field of design. Hum Organ 377–388

Wilson A (2015) A guide to phenomenological research. Nurs Stand 29:38

Wlazlak P, Eriksson Y, Johansson G, Ahlin P (2019) Visual representations for communication in geographically distributed new product development projects. J Eng Des 30:385–403. https://doi.org/10.1080/09544828.2019.1661362

Wood AE, Mattson CA (2019) Quantifying the effects of various factors on the utility of design ethnography in the developing world. Res Eng Des 30:317–338. https://doi.org/10.1007/s00163-018-00304-2

Yang S, Santoro F, Sulthan MA, Zhao YF (2019) A numerical-based part consolidation candidate detection approach with modularization considerations. Res Eng Des 30:63–83. https://doi.org/10.1007/s00163-018-0298-3

Yin RK (2009) Case study research: design and methods, 4th edn. Sage Publications, Thousand Oaks

Zhang X, Thomson V (2019) Modelling the development of complex products using a knowledge perspective. Res Eng Des 30:203–226. https://doi.org/10.1007/s00163-017-0274-3

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David Escudero-Mancebo, Nieves Fernández-Villalobos & Óscar Martín-Llorente

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Escudero-Mancebo, D., Fernández-Villalobos, N., Martín-Llorente, Ó. et al. Research methods in engineering design: a synthesis of recent studies using a systematic literature review. Res Eng Design 34 , 221–256 (2023). https://doi.org/10.1007/s00163-022-00406-y

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How to write a research proposal?

Department of Anaesthesiology, Bangalore Medical College and Research Institute, Bengaluru, Karnataka, India

Devika Rani Duggappa

Writing the proposal of a research work in the present era is a challenging task due to the constantly evolving trends in the qualitative research design and the need to incorporate medical advances into the methodology. The proposal is a detailed plan or ‘blueprint’ for the intended study, and once it is completed, the research project should flow smoothly. Even today, many of the proposals at post-graduate evaluation committees and application proposals for funding are substandard. A search was conducted with keywords such as research proposal, writing proposal and qualitative using search engines, namely, PubMed and Google Scholar, and an attempt has been made to provide broad guidelines for writing a scientifically appropriate research proposal.

INTRODUCTION

A clean, well-thought-out proposal forms the backbone for the research itself and hence becomes the most important step in the process of conduct of research.[ 1 ] The objective of preparing a research proposal would be to obtain approvals from various committees including ethics committee [details under ‘Research methodology II’ section [ Table 1 ] in this issue of IJA) and to request for grants. However, there are very few universally accepted guidelines for preparation of a good quality research proposal. A search was performed with keywords such as research proposal, funding, qualitative and writing proposals using search engines, namely, PubMed, Google Scholar and Scopus.

Five ‘C’s while writing a literature review

BASIC REQUIREMENTS OF A RESEARCH PROPOSAL

A proposal needs to show how your work fits into what is already known about the topic and what new paradigm will it add to the literature, while specifying the question that the research will answer, establishing its significance, and the implications of the answer.[ 2 ] The proposal must be capable of convincing the evaluation committee about the credibility, achievability, practicality and reproducibility (repeatability) of the research design.[ 3 ] Four categories of audience with different expectations may be present in the evaluation committees, namely academic colleagues, policy-makers, practitioners and lay audiences who evaluate the research proposal. Tips for preparation of a good research proposal include; ‘be practical, be persuasive, make broader links, aim for crystal clarity and plan before you write’. A researcher must be balanced, with a realistic understanding of what can be achieved. Being persuasive implies that researcher must be able to convince other researchers, research funding agencies, educational institutions and supervisors that the research is worth getting approval. The aim of the researcher should be clearly stated in simple language that describes the research in a way that non-specialists can comprehend, without use of jargons. The proposal must not only demonstrate that it is based on an intelligent understanding of the existing literature but also show that the writer has thought about the time needed to conduct each stage of the research.[ 4 , 5 ]

CONTENTS OF A RESEARCH PROPOSAL

The contents or formats of a research proposal vary depending on the requirements of evaluation committee and are generally provided by the evaluation committee or the institution.

In general, a cover page should contain the (i) title of the proposal, (ii) name and affiliation of the researcher (principal investigator) and co-investigators, (iii) institutional affiliation (degree of the investigator and the name of institution where the study will be performed), details of contact such as phone numbers, E-mail id's and lines for signatures of investigators.

The main contents of the proposal may be presented under the following headings: (i) introduction, (ii) review of literature, (iii) aims and objectives, (iv) research design and methods, (v) ethical considerations, (vi) budget, (vii) appendices and (viii) citations.[ 4 ]

Introduction

It is also sometimes termed as ‘need for study’ or ‘abstract’. Introduction is an initial pitch of an idea; it sets the scene and puts the research in context.[ 6 ] The introduction should be designed to create interest in the reader about the topic and proposal. It should convey to the reader, what you want to do, what necessitates the study and your passion for the topic.[ 7 ] Some questions that can be used to assess the significance of the study are: (i) Who has an interest in the domain of inquiry? (ii) What do we already know about the topic? (iii) What has not been answered adequately in previous research and practice? (iv) How will this research add to knowledge, practice and policy in this area? Some of the evaluation committees, expect the last two questions, elaborated under a separate heading of ‘background and significance’.[ 8 ] Introduction should also contain the hypothesis behind the research design. If hypothesis cannot be constructed, the line of inquiry to be used in the research must be indicated.

Review of literature

It refers to all sources of scientific evidence pertaining to the topic in interest. In the present era of digitalisation and easy accessibility, there is an enormous amount of relevant data available, making it a challenge for the researcher to include all of it in his/her review.[ 9 ] It is crucial to structure this section intelligently so that the reader can grasp the argument related to your study in relation to that of other researchers, while still demonstrating to your readers that your work is original and innovative. It is preferable to summarise each article in a paragraph, highlighting the details pertinent to the topic of interest. The progression of review can move from the more general to the more focused studies, or a historical progression can be used to develop the story, without making it exhaustive.[ 1 ] Literature should include supporting data, disagreements and controversies. Five ‘C's may be kept in mind while writing a literature review[ 10 ] [ Table 1 ].

Aims and objectives

The research purpose (or goal or aim) gives a broad indication of what the researcher wishes to achieve in the research. The hypothesis to be tested can be the aim of the study. The objectives related to parameters or tools used to achieve the aim are generally categorised as primary and secondary objectives.

Research design and method

The objective here is to convince the reader that the overall research design and methods of analysis will correctly address the research problem and to impress upon the reader that the methodology/sources chosen are appropriate for the specific topic. It should be unmistakably tied to the specific aims of your study.

In this section, the methods and sources used to conduct the research must be discussed, including specific references to sites, databases, key texts or authors that will be indispensable to the project. There should be specific mention about the methodological approaches to be undertaken to gather information, about the techniques to be used to analyse it and about the tests of external validity to which researcher is committed.[ 10 , 11 ]

The components of this section include the following:[ 4 ]

Population and sample

Population refers to all the elements (individuals, objects or substances) that meet certain criteria for inclusion in a given universe,[ 12 ] and sample refers to subset of population which meets the inclusion criteria for enrolment into the study. The inclusion and exclusion criteria should be clearly defined. The details pertaining to sample size are discussed in the article “Sample size calculation: Basic priniciples” published in this issue of IJA.

Data collection

The researcher is expected to give a detailed account of the methodology adopted for collection of data, which include the time frame required for the research. The methodology should be tested for its validity and ensure that, in pursuit of achieving the results, the participant's life is not jeopardised. The author should anticipate and acknowledge any potential barrier and pitfall in carrying out the research design and explain plans to address them, thereby avoiding lacunae due to incomplete data collection. If the researcher is planning to acquire data through interviews or questionnaires, copy of the questions used for the same should be attached as an annexure with the proposal.

Rigor (soundness of the research)

This addresses the strength of the research with respect to its neutrality, consistency and applicability. Rigor must be reflected throughout the proposal.

It refers to the robustness of a research method against bias. The author should convey the measures taken to avoid bias, viz. blinding and randomisation, in an elaborate way, thus ensuring that the result obtained from the adopted method is purely as chance and not influenced by other confounding variables.

Consistency

Consistency considers whether the findings will be consistent if the inquiry was replicated with the same participants and in a similar context. This can be achieved by adopting standard and universally accepted methods and scales.

Applicability

Applicability refers to the degree to which the findings can be applied to different contexts and groups.[ 13 ]

Data analysis

This section deals with the reduction and reconstruction of data and its analysis including sample size calculation. The researcher is expected to explain the steps adopted for coding and sorting the data obtained. Various tests to be used to analyse the data for its robustness, significance should be clearly stated. Author should also mention the names of statistician and suitable software which will be used in due course of data analysis and their contribution to data analysis and sample calculation.[ 9 ]

Ethical considerations

Medical research introduces special moral and ethical problems that are not usually encountered by other researchers during data collection, and hence, the researcher should take special care in ensuring that ethical standards are met. Ethical considerations refer to the protection of the participants' rights (right to self-determination, right to privacy, right to autonomy and confidentiality, right to fair treatment and right to protection from discomfort and harm), obtaining informed consent and the institutional review process (ethical approval). The researcher needs to provide adequate information on each of these aspects.

Informed consent needs to be obtained from the participants (details discussed in further chapters), as well as the research site and the relevant authorities.

When the researcher prepares a research budget, he/she should predict and cost all aspects of the research and then add an additional allowance for unpredictable disasters, delays and rising costs. All items in the budget should be justified.

Appendices are documents that support the proposal and application. The appendices will be specific for each proposal but documents that are usually required include informed consent form, supporting documents, questionnaires, measurement tools and patient information of the study in layman's language.

As with any scholarly research paper, you must cite the sources you used in composing your proposal. Although the words ‘references and bibliography’ are different, they are used interchangeably. It refers to all references cited in the research proposal.

Successful, qualitative research proposals should communicate the researcher's knowledge of the field and method and convey the emergent nature of the qualitative design. The proposal should follow a discernible logic from the introduction to presentation of the appendices.

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Conflicts of interest.

There are no conflicts of interest.