



ASML is developing state-of-the-art technology for the semiconductor industry. Reliability of our systems is of key importance to our customers. Accurate reliability insights from field data contribute to a wide range of activities, such as stocking planning, service contracts, and design improvements. To enable our engineers to perform analyses fast and efficiently, we have an in-house developed library in python to perform flexible deepdives with a very specific scope depending on the requirements. Currently this library allows experienced engineers to quickly support reliability goals and support other departments with the gained insights by use of Jupyter-notebooks. This library furthermore standardizes the WoW in cleaning and manipulating our data sources, while at the same time reducing the maintenance effort. One of our operational projects is still relying heavily on an extensive Excel script with many macro's behind it, make it slow in processing and not future-proof. The already available and internally developed python reliability package provides all data processing steps and the majority of the required interfaces to build a GUI which can be used by engineers without requiring detailed programming skills. This project will focus on migrating the old excel file into the Python package. There are several steps for the internship: * Talk with the engineers to understand the workings and operational needs of the existing Excel file, and draft a list of requirements for all functionalities needed (and desired in the future); * Build a prototype interface based on the existing package, and implement possibly missing elements; * Test and pilot the new prototype, and update based on feedback from the engineers; * Ensure maintainability of prototype by conforming to common PEP (Python Enhancement Proposals) standards like: overall documentation, type hints, docstring, test cases, etc. * Depending on remaining time additional improvements and enhancements can be implemented inside the package as well. This is a Master internship for around 6 months, working 4-5 days per week. This assignment is not suitable for a thesis. The start date is as soon as possible.