- Full time
Apply by: 2023-10-15
PhD on Investigating the Impact of Product Design Complexity on Learning Curves
Are you interested in delving into the exciting realm of industrial engineering and organizational learning? We are offering a unique opportunity for a dedicated and curious individual to undertake a PhD research project that aims to revolutionize how manufacturing plants adapt to the challenges posed by increasingly complex products. Join us as we explore the dynamic interplay between product complexity and learning curves and contribute to real-world solutions for high-tech firms.
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.
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.
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 department of Industrial Engineering and Innovation Sciences and focuses on understanding and improving innovation processes of high-tech firms. 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
PhD Research Project: Investigating the Impact of Product Design Complexity on Learning Curves
In today's fast-paced manufacturing landscape, the demand for sophisticated and innovative high-tech products is on the rise. This has led to a cascade of new products as well as engineering changes and modifications to existing products that both significantly impact the efficiency of manufacturing processes. This PhD project centers around empirical research that will illuminate the relationship between engineering changes, product design complexity, and the learning curves that govern product development and manufacturing cycles.
The PhD project has two core aims:
- Understanding product design's influence on the learning curve: We want to shed light on how decisions made during the product design and product architecture phases impact the learning curves in product development and manufacturing.
- Guiding effective management: By delving into the complexities of product design, architecture, and learning curves, we aim to provide practical recommendations to managers of high-tech firms for reducing development and manufacturing cycle times.
We plan to apply advanced empirical methodologies to unravel the relationships between engineering changes, product complexities and learning curve effects. Our methods include:
- Mapping product design complexity, modularity, and commonality: We will use design structure matrixes (DSMs) and multi-domain matrixes (MDMs) to visualize and operationalize the intricate connections within product and process architecture.
- Experimentation for testing causality between the product design (complexity, modularity, and commonality) and the learning curve in manufacturing: Our (quasi/natural) experiment design will help us decipher causal links between product design properties and learning curve effects.
- Real-life impact analysis: By tapping into secondary data and time series models, we will uncover real-life effects and trends.
Why Join Us?
This research project offers a unique chance to make meaningful contributions to both academia and high-tech industry. By collaborating with experts in systems and industrial engineering, and innovation and operations management, you will be at the forefront of interdisciplinary research. Your findings will directly address challenges faced by engineering organizations and manufacturing plants in innovating and resource planning after introducing new products, offering actionable insights to enhance efficiency and mitigate risks. In addition to the academic and intellectual rewards, the successful candidate will receive:
- Mentoring from seasoned experts in systems and industrial engineering, and innovation and operations management.
- Access to cutting-edge tools and data analysis techniques.
- Opportunities to present research findings at international conferences.
- Opportunities to gain professional experience in industry and academia.
- Opportunities to become an expert in the fields of product design and learning curves.
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.
- We are seeking a candidate with a strong academic background in 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. The ideal candidate should meet the following requirements:
- You possess a unique blend of enthusiasm for both engineering sciences and social sciences, combined with a burning passion for unraveling product design complexity challenges and the fascinating world of organizational learning.
- You hold a master's degree in Innovation Management, Mechanical Engineering, Industrial Engineering, Technology Management, Human-Technology Interaction, Industrial Design, or another related, relevant field.
- You demonstrate a strong affinity for interdisciplinary research.
- Your robust analytical skills are complemented by competencies in quantitative research methods, experimental research, or mixed-method approaches combining qualitative and quantitative data analysis.
- You possess the potential and ambition to evolve into a high-level scholar, contributing significantly to the academic field.
- You are adept at addressing topics that demand both fundamental and applied research skills.
- Your social, communication, and organizational skills enable you to excel in both university and industry settings.
- Fluency in spoken and written English is essential.
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, scale P (min. €2,770 max. €3,539).
- 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.
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.
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.
We invite you to submit a complete application by using the 'apply now'-button on this page. 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 your application and will screen it as soon as we have received it. Screening will continue until the position has been 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.
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