PhD Position Predictive Aircraft Maintenance

Challenge: Predict the minimum failure time of aircraft components

Change: Use both classical data science methods and machine learning

Impact: Safe and more efficient aircraft maintenance

Job description

Imagine you are going on holidays: You take the train to the airport and enjoy a coffee while the aircraft takes off. Though we often don’t think about it, the train, the aircraft and even the coffee machine on the aircraft would not work without maintenance.

In this PhD, you will research a new maintenance strategy, called predictive maintenance, that makes this maintenance more efficient. In predictive maintenance, we use the measurements from sensors around components (measuring for instance the temperature) to predict the time left until the failure of the component (called the Remaining Useful Life, RUL). Your efforts will focus on aircraft predictive maintenance.

We cannot predict the RUL with absolute certainty. You will therefore predict a distribution for the RUL. The challenging, but also fun, part about aircraft maintenance, is that safety is of paramount important. We are therefore specifically interested in predicting the minimum value of the RUL by predicting and modelling the left tail of the RUL distribution. In this way, we can answer questions such as “Is the probability that the component will fail within the next week 1% or 0.1%?”. To do so, you will combine (classical) data science methods with modern machine learning, statistics and methods from the field of extreme value theory and rare event simulation.

This PhD will suit you well if you like to apply mathematics to solve practical problems. However, you also like to dive into the theory behind the mathematical methods, and tweak these methods such that they can be applied to the maintenance domain.

As a PhD candidate, you will become part of the Air Transport & Operations group of the faculty of Aerospace Engineering. You will join an active and social group of PhD students, and a team with a great, colloquial atmosphere.

Requirements

• You have completed or are about to complete a master with a quantitative background, for instance (but not limited to) aerospace engineering with a focus on optimization, econometrics, mathematics or statistics.
• You are good at programming. We use Python, but feel free to apply if you program in another language and don’t mind switching.
• You are proficient in English.
• Due to the expiration date of the funding, you are able to start (and thus have completed your master) before or on 1-1-2025.

Besides this, it is nice, but not required, if you have some knowledge about either maintenance, aviation, statistics, (classical) data science methods, machine learning, rare event simulation or the extreme value theory.

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis.

TU Delft (Delft University of Technology)

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

Faculty Aerospace Engineering

The Faculty of Aerospace Engineering at Delft University of Technology is one of the world’s most highly ranked (and most comprehensive) research, education and innovation communities devoted entirely to aerospace engineering. More than 200 science staff, around 270 PhD candidates and close to 3000 BSc and MSc students apply aerospace engineering disciplines to address the global societal challenges that threaten us today, climate change without doubt being the most important. Our focal subjects: sustainable aerospace, big data and artificial intelligence, bio-inspired engineering and smart instruments and systems. Working at the faculty means working together. With partners in other faculties, knowledge institutes, governments and industry, both aerospace and non-aerospace. Working in field labs and innovation hubs on our university campus and beyond.

Conditions of employment

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2872 per month in the first year to € 3670 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.