Abstract: This presentation will introduce and demo1 a methodology for equipment diagnostics that has been developed by TNO-ESI in collaboration with ASML and Canon Production Printing (CPP). The methodology2 uses generic model-based systems engineering information, such as functional decomposition, inter[1]functional relations and functional deployment on hardware for diagnostic reasoning. A diagnostic assistant uses the information to support service technicians in the field and supports R&D in assessing the diagnosability of a design.
The methodology has been implemented as a prototype Python library for diagnostics, MBDlyb3, mainly to facilitate in validation and to consolidate the methods.
Currently, we continue the development and validation of the methodology with CPP.
1https://youtu.be/TKoa1teGLRk?si=HtTNavKkHrsWuP90
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