"PhD in Operations Management on Sustainable Spare Parts Management Using Additive Manufacturing"

Job Description

Are you driven by the challenge of making supply chains more sustainable? Join us in using techniques from operations research to explore how additive manufacturing can transform spare parts management to a more sustainable operation.

The availability of spare parts is essential for the maintenance, repair, and remanufacturing of equipment, thus increasing their useful life. However, current practices often rely on large inventories and long lead times, leading to waste, high costs, and unsustainable use of materials. Additive manufacturing (AM) offers a promising alternative by enabling on-demand, local, and potentially circular production of spare parts — but effective decision-making frameworks are still lacking.

In this PhD project, you will develop models and methods for sustainable spare parts management using additive manufacturing. You will explore how to:

• Design supply chains that include AM-based remanufacturing facilities.
• Optimize spare parts inventories and ordering decisions.
• Decide what to do with incoming failed parts (e.g., repair, remanufacture, recycle).
• Collaborate with partner organizations to analyze case studies and generate guidelines for practice.

Your work will combine mathematical modelling and case-based research, while contributing to the broader goal of circular and data-driven supply chains. You will apply techniques from operations research, potentially complemented by techniques from artificial intelligence. This project is part of the national Add-reAM program, which brings together academic, industrial, and other partners to explore the role of AM in advancing the circular economy. You will be embedded in the Operations, Planning, Accounting and Control (OPAC) group within the Department of Industrial Engineering and Innovation Sciences (IE&IS) at Eindhoven University of Technology (TU/e), collaborating closely with researchers working on spare parts logistics, supply chain design, and predictive maintenance.

Requirements

• A Master’s degree in Industrial Engineering, Operations Research, Applied Mathematics, or a related field.
• A strong interest in circular supply chains, spare parts logistics, and additive manufacturing.
• Solid skills in mathematical modeling, ideally also in simulation.
• Programming experience (e.g., Python, MATLAB).
• An interest in sustainability and circularity.
• A research-oriented attitude and ability to work independently.
• Strong communication and collaboration skills.
• Fluent in spoken and written English (C1 level).

Conditions of Employment

Fixed-term contract: 4 years. 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 assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks, with a maximum of 15% per year of your employment.
• 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. € 3,059 max. € 3,881).
• 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.

Additional Information

Do you recognize yourself in this profile and would you like to know more? Please contact the intended supervisors of the PhD position, dr.ir. Rob Basten (r.j.i.basten@tue.nl) or prof.dr.ir. Geert-Jan van Houtum (g.j.v.houtum@tue.nl).