The Ministry of Defence in the Netherlands is operating military systems like vehicles, aircraft, helicopters and ships all around the world. The operational conditions of these systems are demanding and vary continuously. To ensure their availability, a lot of maintenance is required, which must be optimized to match the available budgets. More accurate predictions of upcoming failures result in maintenance just-in-time, high availability and low costs. The MaDeSi project aims to develop models, methods and tools that can predict typical failures in military systems, based on the data available (e.g. usage, mission types, sensor data from platform / engine management systems, health and condition monitoring systems, etc.). In the MaDeSi 2.0 project the Netherlands Defence Academy and University of Twente (UT) collaborate with the National Aerospace Center NLR and the Asset Management Control centre (AMC). A PhD position is now available in this project.

In this PhD project, you will focus on deriving quantitative relations between the operational use (and environment) of military systems and the associated degradation behavior. You can achieve this by developing and applying combinations of physics-of-failure models and data-driven (artificial intelligence, machine learning) approaches. In the preceding project some relations have already been derived for specific cases.

The following steps are foreseen in the PhD project
Identification of possible methods to relate usage to degradation, including the requirements for a successful application – physical models, data analytics, experience based relations, etc. (mainly literature review);

• Identification of available data sources (including amount, quality, accessibility) within the Ministry of Defence – usage, mission types, condition monitoring, failure / maintenance registrations, etc. (interviews with users / maintainers);
• Specification of requirements for additional data collection or improved registration / storage of data;
• Development of a library with usage - degradation relations for various systems / components – for each type of method (physics, data, experience, hybrid) a number of cases are expected to be developed, varying across different systems and components at Air force, Army and Navy;
• Generalization of findings – development of a selection method guiding the choice for a specific type of method and assisting in a quick development of additional relations;
• Demonstration / validation of the tools in a pilot project;

This PhD project will focus on scientific advancements in predictive maintenance, aiming to produce a number of scientific journal publications, but at the same time contributes to the development of practical tools (by the project partners) that will improve the maintenance process at the Ministry of Defense.

If you see challenges in combining physics-of-failure models and data analytics methods, we are looking for you. This means that you have a MSc degree in either a technical domain (e.g. Mechanical Engineering, Applied Physics, Materials Science, Systems Engineering) or a data / information domain (e.g. Industrial Engineering, Data Science), but in addition a proven affinity / background in the other domain.

For this position, you should be a team-player with self-reflection who takes initiative. Besides, you have strong social and communication skills and you like to present your work at conferences and project meetings. Fluency in English is required. You need to provide IELTS test results (minimum score 6.5), TOEFL-iBT (minimum score 90) or Cambridge CAE or CPE. An interview and a scientific presentation is part of the selection procedure.

More information

• For more information on the research at the Twente is Maintenance Excellence (TIME) consortium in general you can visit www.utwente.nl/time
• For information about Dynamics based Maintenance group in particular, please visit www.utwente.nl/ctw/tm/research/DBM
• For additional information about this specific vacancy you can send an email to prof.dr.ir. Tiedo Tinga; t.tinga@utwente.nl.

Your application

• Your application should comprise:
• a letter of motivation
• a curriculum vitae
• a list with grades of courses attended
• contact information of 2 referees
• if applicable, a list of publications.

The intended start of the project is summer 2018. The location will be (a combination of) the facilities of the NLDA in Den Helder and the UT. As the project is executed within the Ministry of Defence, a security screening is part of the procedure and citizenship of a NATO country is required.

Applications should be submitted before July 7, 2018

• We offer a 4-year full-time position as a PhD candidate appointed at the University of Twente, with a qualifier within 1 year. Your starting salary will be € 2222 gross per month in the first year and up to € 2840 gross per month in the final year;
• A holiday allowance of 8% of the gross annual salary and a year-end bonus of 8.3%;
• Minimum of 29 leave days in case of full-time employment;
• A solid pension scheme;

The University of Twente. We stand for life sciences and technology. High tech and human touch. Education and research that matter. New technology which leads change, innovation and progress in society. The University of Twente is the only campus university of the Netherlands; divided over five faculties we provide more than fifty educational programmes. We have a strong focus on personal development and talented researchers are given scope for carrying out groundbreaking research.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status or disability status. Because of our diversity values we do particularly support women to apply.

The Faculty of Engineering Technology (ET) is one of the five faculties of the University of Twente. ET combines Mechanical Engineering, Civil Engineering and Industrial Design Engineering. Our faculty has approximately 1800 bachelor and master students, 400 employees and 150 PhD candidates. The departments of the faculty cooperatively conduct the educational programmes and participate in interdisciplinary research projects, programmes and the research institutes: MIRA, CTIT, SBE and IGS.