PhD candidate in predictive maintenance service logistics
PhD candidate in predictive maintenance service logistics
You cannot apply for this job anymore (deadline was 6 Oct 2019).
Browse the current job offers or choose an item in the top navigation above.
Job description
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. Researchers are member of the Beta research school.
Group
The open position is at the Operations Planning, Accounting & Control group (OPAC). OPAC currently consists of 5 full professors, 5 associate professors, 15 assistant professors, 10 postdoctoral fellows, and 30 PhD candidates. The faculty teaches and conducts research in the area of operations planning and control in manufacturing, maintenance services, logistics and supply chains. Research is generally quantitative in nature, while many of the researchers also engage in empirical research. The OPAC group is responsible within the university for all teaching in the areas of operations management, transportation, manufacturing operations, reliability and maintenance, and accounting and finance, both at undergraduate and graduate level. The OPAC group has an extensive industrial network, which gives direct access to challenging operations management problems, new technologies, and empirical data.
PrimaVera project
The PhD position is part of the PrimaVera project that has a budget of 5 M€ and is funded by NWO and co-funded by a large number of companies and other organizations from the Netherlands (the exact consortium can be found in this news article). PrimaVera aims to make a significant step forward in the area of predictive maintenance (PM). PM is the ability to use data-driven analytics to optimize the upkeep of capital equipment: To create value by transforming collected data from intelligent systems into predictions about the system's health, by avoiding future failures through just-in-time maintenance, by doing maintenance exactly when and where needed, according to the specific needs of the system and according to its specification. PM is widely seen as one of the most valuable applications of the Internet of Things. Furthermore, PM is a key enabling technology for servitization in smart industries. Servitization is an emerging trend in which organizations and citizens no longer own assets, but rather lease their services: companies buy hours on production machineries with a guaranteed throughput; people lease cars rather than buying one. As a consequence, the asset service providers have to guarantee a continuous service. Servitization mandates constant availability at a low cost, prescriptive (personalised) service, and full digitization and automation of service provision. Thus, the benefits of PM are tremendous. However, realizing the envisioned benefits is far from trivial. Companies experience major obstacles in leveraging PM technologies, and achieving a cross-functional working culture. Dismantling these obstacles demands tackling three game changers concerning the entire PM cycle: Accurate health prognostics leading to effective maintenance decisions, holistic PM workflow plans in a complex arena, and automation of the solution. Tackling these game changers requires different expertises to work closely together. We have a number of vacancies on this project.
PhD project
The goal of this PhD project is to develop accurate, efficient, effective, and robust methods for large-scale maintenance optimization and simultaneous service logistics control, i.e., the control of all activities required to ensure availability of spare parts, tooling, and service engineers when maintenance needs to be performed. The link between maintenance optimization and service logistics control has recently received considerable attention, as performing maintenance is not possible when, for example, spare parts are unavailable. Integrating the two objectives through multi-level optimization is expected to significantly lower costs, as the solutions to the independent optimization problems do not lead to a global optimum. It is notable that each problem viewed separately is complex and hard, thus integrating the two objectives will make the problem arduous. Still some simpler problems (e.g., optimization for one single asset) may permit exact analysis using techniques from stochastic (spare parts) inventory management. These simple problems will provide the necessary insights for the complex realistic industrial frameworks under consideration and for the case of fleets of assets or systems. For the complex realistic models, we will extend the results obtained recently in large-scale asset level maintenance optimization.
Job description
You, as a successful applicant, will perform the PhD project outlined above in an international team and in close collaboration with industry. The research will be concluded with a PhD thesis. You will be supervised by dr.ir. Rob Basten and prof.dr.ir. Geert-Jan van Houtum. A small teaching load is part of the job.
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. Researchers are member of the Beta research school.
Group
The open position is at the Operations Planning, Accounting & Control group (OPAC). OPAC currently consists of 5 full professors, 5 associate professors, 15 assistant professors, 10 postdoctoral fellows, and 30 PhD candidates. The faculty teaches and conducts research in the area of operations planning and control in manufacturing, maintenance services, logistics and supply chains. Research is generally quantitative in nature, while many of the researchers also engage in empirical research. The OPAC group is responsible within the university for all teaching in the areas of operations management, transportation, manufacturing operations, reliability and maintenance, and accounting and finance, both at undergraduate and graduate level. The OPAC group has an extensive industrial network, which gives direct access to challenging operations management problems, new technologies, and empirical data.
PrimaVera project
The PhD position is part of the PrimaVera project that has a budget of 5 M€ and is funded by NWO and co-funded by a large number of companies and other organizations from the Netherlands (the exact consortium can be found in this news article). PrimaVera aims to make a significant step forward in the area of predictive maintenance (PM). PM is the ability to use data-driven analytics to optimize the upkeep of capital equipment: To create value by transforming collected data from intelligent systems into predictions about the system's health, by avoiding future failures through just-in-time maintenance, by doing maintenance exactly when and where needed, according to the specific needs of the system and according to its specification. PM is widely seen as one of the most valuable applications of the Internet of Things. Furthermore, PM is a key enabling technology for servitization in smart industries. Servitization is an emerging trend in which organizations and citizens no longer own assets, but rather lease their services: companies buy hours on production machineries with a guaranteed throughput; people lease cars rather than buying one. As a consequence, the asset service providers have to guarantee a continuous service. Servitization mandates constant availability at a low cost, prescriptive (personalised) service, and full digitization and automation of service provision. Thus, the benefits of PM are tremendous. However, realizing the envisioned benefits is far from trivial. Companies experience major obstacles in leveraging PM technologies, and achieving a cross-functional working culture. Dismantling these obstacles demands tackling three game changers concerning the entire PM cycle: Accurate health prognostics leading to effective maintenance decisions, holistic PM workflow plans in a complex arena, and automation of the solution. Tackling these game changers requires different expertises to work closely together. We have a number of vacancies on this project.
PhD project
The goal of this PhD project is to develop accurate, efficient, effective, and robust methods for large-scale maintenance optimization and simultaneous service logistics control, i.e., the control of all activities required to ensure availability of spare parts, tooling, and service engineers when maintenance needs to be performed. The link between maintenance optimization and service logistics control has recently received considerable attention, as performing maintenance is not possible when, for example, spare parts are unavailable. Integrating the two objectives through multi-level optimization is expected to significantly lower costs, as the solutions to the independent optimization problems do not lead to a global optimum. It is notable that each problem viewed separately is complex and hard, thus integrating the two objectives will make the problem arduous. Still some simpler problems (e.g., optimization for one single asset) may permit exact analysis using techniques from stochastic (spare parts) inventory management. These simple problems will provide the necessary insights for the complex realistic industrial frameworks under consideration and for the case of fleets of assets or systems. For the complex realistic models, we will extend the results obtained recently in large-scale asset level maintenance optimization.
Job description
You, as a successful applicant, will perform the PhD project outlined above in an international team and in close collaboration with industry. The research will be concluded with a PhD thesis. You will be supervised by dr.ir. Rob Basten and prof.dr.ir. Geert-Jan van Houtum. A small teaching load is part of the job.
Specifications
- max. 38 hours per week
- Eindhoven View on Google Maps
:fill(white)/logos/tue-en-wide_acOLN2b.png)
Eindhoven University of Technology (TU/e)
Requirements
You have:
- A Master's degree in Operations Research, Econometrics, Industrial Engineering, Operations Management, Applied Mathematics, or a related field.
- Strong affinity with interdisciplinary research, as well as collaboration with industry.
- Strong analytical skills and demonstrated competence for quantitative modeling.
- Potential and ambition to become a top-level management scholar.
- The ability to work on a challenging topic that has both fundamental and applied research aspects.
- Verbal and written communication skills that are excellent, as is your proficiency in English and your ability to collaborate in an international setting.
Conditions of employment
We offer:
- A challenging job in a dynamic and ambitious university.
- A PhD appointment for a period of 4 years.
- A gross monthly salary of €2.325,- in the first year up to €2.972,- (gross) in the fourth year on a full-time basis.
- A yearly holiday allowance of 8% and 8.3% end of year allowance.
- A broad package of fringe benefits (including an excellent technical infrastructure, moving expenses, savings schemes, coverage of costs of publishing the dissertation and excellent sports facilities).
