Internship | Stochastic Modeling Intern

Internship in Stochastic Modeling

About this position

In the world of modern high-tech manufacturing, increasing demand on system performance translates into an increasing need for flexibility and precision on all levels, including robotic control and machine logistics, and leads to increased complexity. With the old methods of hand-crafted modelling of machine logistics struggling to keep up with such requirements, formal modelling frameworks of machine logistics such as LSAT or dataflow graphs have become a valuable tool for design engineers. Yet, current models do not account for the inherent uncertainty of real-world processes, e.g. timing variations or unplanned maintenance, which forces designers to rely on heuristics and make compromises such as designing for worst case scenario. Significant performance could thus be gained by accounting for the system’s uncertainty sources and tracking how this uncertainty propagates, for example, by computing how unexpected delays affect the timing of successive actions and the length of the production cycle.

What will be your role?

In a model-based design of a machine’s logistics, such as those captured as LSAT or dataflow models, the scheduling of actions within given activities links closely to activity graphs found in standardized modeling languages like UML/SysML. Computing the start and end-times of nodes in such activity graphs is a key step towards analyzing the overall productivity of a flexible manufacturing system. In this project, the student will adapt and extend the modelling frameworks of LSAT and/or dataflow graphs to the computation of timings with stochastic machine behavior.

The student will be encouraged to explore different approaches to compute the stochastic timing behavior of activity graphs such as MCMC sampling, extreme value theory or variational message passing on factor graphs.

Along with theory development, the project will include implementation in code and validation on test-cases inspired by real-world cases from the Dutch high-tech industry. This master’s project will be part of the WLSAT-NG project in collaboration with TU/e, TNO-ESI, ASML and VDL-ETG.

What we expect from you

A background in electrical engineering, applied mathematics or computer science is preferable. Knowledge of probability theory, stochastic processes and/or model-based design is also strongly suggested.

The project will take place at TNO-ESI under a TNO internship contract and will be co-supervised by the Model-Based Design Lab of the Technical University of Eindhoven (TU/e) and the LSAT team at TNO-ESI.

What you'll get in return

• A highly professional, innovative internship environment, within a team of top experts.
• A suitable internship allowance (615 euro for wo-, hbo- and mbo-students, for a full-time internship).
• Possibility of eight hours of free leave per internship month (for a full-time internship).
• A free membership of Jong TNO, where you can meet other TNO professionals and join several activities, such as sports activities, (work-related) courses or the yearly ski-trip.
• Use of a laptop.
• An allowance for travel expenses in case you don’t receive an OV-card.

TNO as an employer

At TNO, we innovate for a healthier, safer and more sustainable life. And for a strong economy. Since 1932, we have been making knowledge and technology available for the common good. We find each other in wonder and ingenuity. We are driven to push boundaries. There is all the space and support for your talent and ambition. You work with people who will challenge you: who inspire you and want to learn from you. Our state-of-the-art facilities are there to realize your vision. What you do at TNO matters: impact makes the difference. Because with every innovation you contribute to tomorrow’s world.

At TNO we encourage an inclusive work environment, where you can be yourself. Whatever your story and whatever unique qualities you bring to the table. It is by combining our unique strengths and perspectives that we are able to develop innovations that make a real difference in society.

Contact

• Alvaro Piedrafita Postigo
  • E-mailadres: alvaro.piedrafitapostigo@tno.nl