Data analytics for time constraint adherence prediction in a semiconductor manufacturing use-case
نویسندگان
چکیده
Semiconductor manufacturing represents a challenging industrial environments, where products require more than several hundred operations, each representing the technical state-of-the-art. Products vary greatly in volume, design and required production processes and, additionally, product portfolios technologies change rapidly. Thus, technologically restricted rapid development, stringent quality related clean room requirements high precision equipment application enforce operational excellence, particular time constraints adherence. Product specific between two or successive process operations are an industry-specific challenge, as violations lead to additional scrapping reworking costs. Time constraint adherence is linked dispatching currently manually assessed. To overcome this error-prone manual task, article presents data-based decision predict semiconductor manufacturing. Real-world historical data analyzed appropriate statistical models scoring functions derived. Compared other relevant literature regarding violations, central contribution of design, generation validation model for quality-related based on real-world plant.
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ژورنال
عنوان ژورنال: Procedia CIRP
سال: 2021
ISSN: ['2212-8271']
DOI: https://doi.org/10.1016/j.procir.2021.05.008