Maintenance Shop Planning Optimization - Graduation Project

Background

Maintenance, Repair and Overhaul (MRO) activities form an important part of aviation. In order to facilitate Continuous Airworthiness, it is important that MRO activities happen regularly to aircraft. For aircraft operators, this means that an aircraft is not available to earn money. The costs for this unavailability increase very quickly and to keep these under control, it is important that maintenance happens in an efficient and timely manner.

Conducting MRO activities in a timely and efficient manner requires the coordination of many different other aspects. A shop needs facilities, tools, spare parts and people to be combined in order to generate maintenance opportunities, for a wide range of maintenance tasks on many types of planes. The manpower, materials and facilities and tools need to be available at the same time for the right task to make sure that a plane can be maintained. This makes the planning and scheduling of maintenance activities for aviation complex challenges with many variables and much data to keep track of.

At NLR we aim to support MRO organisations and Aviation operators in finding smart solutions to manage the complexity of this planning task. This support includes the development of smart heuristics, smart models and smart algorithms to deal with the planning problems of MRO organisations. These models and algorithms also require validation based on data analytics, and given the experimental nature and broad scope of the assignment, this offers a nice opportunity for a master thesis topic related to Data Analytics. Your assignment will be to conduct research how Aviation MRO shop job scheduling can be planned and the planning be optimized.

Assignment

• Research heuristics for efficient scheduling of Aviation Maintenance Activities in a MRO shop
• Research an algorithmic method to schedule maintenance capacity of a MRO shop efficiently
• Build a model in C-sharp to assess and validate the heuristics and the algorithmic method

Result

• Scientific research report describing the applied methods, findings and recommendations
• C-sharp code containing a working model, and accompanying documentation
• Your graduation from University.

Duration

6-9 months, starting from February

Profile

• WO Master in Data analytics or equivalent field of study
• Preferably background in programming in C Sharp
• Affinity with industrial engineering is a plus
• Assertive and self-motivated, able to be part of the project team and also proceed individually

What we offer

• A challenging graduation project/internship in a high-tech result oriented work environment
• Weekly supervision and availability of the technical staff for support
• An internship allowance
• Working in an actual R&D project as part of the team
• Internship results to be used in the current and future projects

About NLR

Royal NLR has been the ambitious research organisation with the will to keep innovating for over 100 years. With that drive, we make the world of transportation safer, more sustainable, more efficient and more effective. We are on the threshold of breakthrough innovations. Plans and ideas start to move when these are fed with the right energy. Over 800 driven professionals work on research and innovation. From aircraft engineers to psychologists and from mathematicians to application experts.

Our colleagues are happy to tell you what it’s like to work at NLR.

Hier nog wat info over de afdeling bijvoorbeeld:
This assignment will be managed by the Maintenance Engineering group of the Avionics Systems and Maintenance Engineering (ASAM) department of NLR.

Interested?

Apply below! Have questions? Contact recruitment@nlr.nl +31(0)885114201 for more information.