The School of Industrial Engineering is one of the longest-established IE Schools in Europe, with a strong presence in the international research, design, and education community, especially in the field of Operations Management and Operations Research. OM and OR are at the core of the undergraduate IE program. The graduate programs (MSc, PDEng, and PhD) in Operations Management & Logistics attract top-level candidates from all over the world. The research and education at the OPAC group of the School of Industrial Engineering has specific emphasis on:

Planning and Control in Manufacturing, Services, and Supply Chains;

Distribution Logistics;

Maintenance and Reliability;

Finance and Accounting, oriented towards operational processes.

The group is currently looking for a Postdoc to perform a top level research project in close collaboration with industry in the area of condition based spare parts inventory conrol.

Tasks
The Postdoc is expected to perform top level research for one year (duration of up to one and a half year can be discussed) in the focus area Maintenance and Reliability, more specifically on condition based spare parts inventory control. The research will be performed in collaboration with industry, together with prof.dr.ir. G.J. van Houtum and dr.ir. R.J.I. Basten.

Project Background
During the long life cycle of capital goods, such as radar systems, baggage handling systems, poultry processing lines, and professional printers, maintenance needs to be performed. Timely maintenance is important in order to keep the capital goods operational and the primary process of its user going. Maintenance can be performed upon failure, i.e., corrective maintenance, or it can be performed every so many weeks, i.e., time based maintenance. Increasingly, condition based maintenance is used, which means that maintenance is performed when a certain measured condition reaches a certain threshold. The measured condition can be vibrations or parts in oil samples, for example. Application of condition based maintenance, also called predictive maintenance, complicates planning of maintenance for multi-component systems, and it requires high responsiveness from the service logistics, i.e., all processes that are required in order to get spare parts, service engineers, equipment, etc. at the right time at the right place. In this project, we aim to develop models that can be used to perform condition based spare parts supply, i.e., spare parts inventory control using condition monitoring information that is generated by capital goods in the field. Our models should be useful in practice and for that reason, we get inspiration from a few companies, especially Océ, Marel Stork and Vanderlande. One of the ways to do this is by having Bachelor and Master students work at these companies. The Postdoc is expected to be involved in these student projects and to derive insights from them that result in newly developed condition based spare parts inventory control models that can be published in top journals. This Postdoc position is part of the so-called ProSeLoNext project, in which we collaborate with twelve parties (three other universities and nine companies).

For this Postdoc position, the applicant should have completed (or be close to completion of) a PhD degree in operations management, operations research, econometrics, mathematics, or industrial engineering, with a solid background in quantitative research methods. Candidates should have a good basis in stochastic modeling such as inventory control, quality control, and stochastic processes. It is an advantage to also have knowledge on mechanical or electrical engineering or a related discipline. Fluency in English is required. The candidate should further be interested in cooperation with companies.

We offer:

a challenging job in a dynamic and ambitious university;

an appointment for a period of 18 months;

a gross monthly salary between € 3.111 and € 4.084, based on a full-time appointment and depending on experience and knowledge;

a yearly holiday allowance of 8% of the yearly salary;

a yearly end year allowance of 8.3% of the yearly salary;

a broad package of fringe benefits (including an excellent technical infrastructure, moving expenses, savings schemes, and excellent sports facilities).