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PhD on the product design learning curve

PhD on the product design learning curve

Position
PhD-student
Irène Curie Fellowship
No
Department(s)
Industrial Engineering and Innovation Sciences
FTE
1,0
Date off
15/02/2023
Reference number
V39.6142

Job description

Eindhoven University of Technology is looking for a PhD candidate with a master’s degree in one (or more) of the following programs:  Innovation Management, Mechanical Engineering, Industrial Engineering, Technology Management, Human-Technology Interaction, or Industrial Design, and with an interest in quantitative and qualitative empirical research on the interface of Product Design, Innovation, and Operations Management.

Organization
Eindhoven University of Technology is one of the world’s leading research universities (ranked by the Times Higher Education Supplement) and is particularly well known for its joint research with industry (ranked number one worldwide by the Centre for Science and Technology Studies). The Department of Industrial Engineering & Innovation Sciences (IE&IS) of Eindhoven University of Technology is one of the longest-established engineering schools in Europe, with a strong presence in the international research and education community, especially in the fields of Operations Management and Innovation Management, which are at the core of the undergraduate BSc program. The graduate programs (MSc and PhD) in Operations Management & Logistics and Innovation Management attract top-level students from all over the world.

Group
The PhD project is conducted within the Innovation, Technology Entrepreneurship & Marketing (ITEM) group in close collaboration with the Control Systems Technology (CST) group. The ITEM group is part of the School of Industrial Engineering of the department IE&IS. The ITEM group focuses on managing innovation processes and new product development, including marketing of new products and marketing analytics. The CST group is part of the department Mechanical Engineering, and focuses on performance-driven design and control of high-tech engineering systems.

Short description of the PhD Project
“Improving knowledge flows between design and manufacturing through optimization of product and process architecture mapping”

To keep up with market demands, companies continuously improve their product designs. However, every adjustment to product designs disrupts manufacturing as tools and processes must be updated and possibly redesigned, and employees must adapt to the new situation. Most companies have difficulty estimating the extent of this disruption, but the complexity of this design change seems to be an important determining factor. It is widely known that product design choices directly impact how a product is manufactured. A modular product design provides opportunities for setting up independent work centres based on grouping technologies or clustering tasks strongly interfacing with each other. Commonality within product architecture design offers opportunities for reuse in manufacturing and repeat specific processes. More commonality can also provide scale effects and reduction of costs.

Furthermore, manufacturing performance has long been known to display learning effects: As an organization gains experience producing a particular product, its performance improves. By disrupting the manufacturing process, product design changes may impede this ongoing learning process. An improved understanding of the impact of product architecture design changes on learning in manufacturing could form the basis of better production planning and improved resource allocation. In this research project, the first goal is therefore to investigate how product design choices influence the learning rate in development and manufacturing.

What is more, a well-known hypothesis is that an organization's formal structure should "mirror" the design of the underlying technical system. That is, the organizational links (e.g., communication, collocation, employment relationships) should match the technical dependencies in the work being performed. We note here that this mirroring also optimizes the flow of information. Namely, provided that the product design has a particular architecture and a related manufacturing process, it is advantageous for the flow of knowledge between development and manufacturing that the process architecture mirrors the product architecture. This mirroring is expected to result in an improved knowledge flow between development engineers and operators belonging to the same functional or technical cluster of the product, positively affecting the learning curves in development and manufacturing. In this research project, the second goal is to investigate this mirroring effect on learning curves of and knowledge transfer between development and manufacturing.

This project is set up to research the impacts of technological complexity on performance. The PhD project seeks (1) to better understand the impact of design and product architecture decisions on development and manufacturing learning curves, and (2) to develop policy recommendations on how to improve the management of product design, product architecture, and learning curve decisions. The proposed methodologies include: mapping the product and process architecture using design structure matrixes (DSMs) and multi-domain matrixes (MDMs), (quasi/natural) experiment design to test causality between product design properties and learning curve effects, and an analysis of real-life effects using secondary data and time series models, amongst other methods.

Job description
You, as a successful applicant, will perform the research project outlined above in an international team. The research will be concluded with a PhD thesis. A small teaching load is part of the job.

Job requirements

  • You have a master’s degree in Innovation Management, Mechanical Engineering, Industrial Engineering, Technology Management, Human-Technology Interaction, or Industrial Design, or another related, relevant field. 
  • You have a strong affinity with interdisciplinary research, as well as collaboration with industry.
  • You have strong analytical skills and demonstrated competencies in quantitative, experimental research methods, or mixed method approaches combining qualitative and quantitative data analysis.
  • Potential and ambition to become a high-level management scholar.
  • You can work on a topic that requires both basic and applied research skills.
  • You have excellent social, communication and organization skills to work effectively in a university and industry setting.
  • You are fluent in spoken and written English. The ability to speak Dutch is highly appreciated.

Conditions of employment

A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:

  • Full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months. You will spend 10% of your employment on teaching tasks.
  • Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities.
  • A year-end bonus of 8.3% and annual vacation pay of 8%.
  • High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
  • An excellent technical infrastructure, on-campus children's day care and sports facilities.
  • An allowance for commuting, working from home and internet costs.
  • A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.

Information and application

About us

Eindhoven University of Technology is an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top-five position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow. 

Information

Do you recognize yourself in this profile and would you like to know more?
Please contact dr. Alex Alblas (a.a.alblas[at]tue.nl), prof.dr. Fred Langerak (f.langerak[at]tue.nl) or Pascal Etman (l.f.p.etman[at]tue.nl).

Visit our website for more information about the application process or the conditions of employment. You can also contact Najat Loiazizi, personnel officer (HRServices.IEIS[at]tue.nl).

Are you inspired and would like to know more about working at TU/e? Please visit our career page.

Application

We invite you to submit a complete application by using the apply button. The application should include a:

  • Cover letter (2-page max.), which includes your motivation and an explanation of why you would fit well with the project.
  • Detailed curriculum vitae, including an elaboration of your experience in quantitative methodologies (e.g., statistics and/or experiments) and qualitative methodologies (e.g., case studies, natural/field experiments).
  • List of courses taken in master and bachelor programs (incl. grades).
  • Brief description of your MSc thesis.
  • Results of a recent English language test, or other evidence of your English language capabilities (TOEFL, IELTS, etc.).
  • Name and contact information of two references.

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.

We do not respond to applications that are sent to us in a different way. Please keep in mind you can upload only 5 documents up to 2 MB each. If necessary, please combine files.