Managing product-inherent constraints with artificial intelligence: production control for time constraints in semiconductor manufacturing

Marvin Carl May (), Jan Oberst and Gisela Lanza
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Marvin Carl May: Karlsruhe Institute of Technology (KIT)
Jan Oberst: Karlsruhe Institute of Technology (KIT)
Gisela Lanza: Karlsruhe Institute of Technology (KIT)

Journal of Intelligent Manufacturing, 2024, vol. 35, issue 8, No 33, 4259-4276

Abstract: Abstract Continuous product individualization and customization led to the advent of lot size one in production and ultimately to product-inherent uniqueness. As complexities in individualization and processes grow, production systems need to adapt to unique, product-inherent constraints by advancing production control beyond predictive, rigid schedules. While complex processes, production systems and production constraints are not a novelty per se, modern production control approaches fall short of simultaneously regarding the flexibility of complex job shops and product unique constraints imposed on production control. To close this gap, this paper develops a novel, data driven, artificial intelligence based production control approach for complex job shops. For this purpose, product-inherent constraints are resolved by restricting the solution space of the production control according to a prediction based decision model. The approach validation is performed in a real semiconductor fab as a job shop that includes transitional time constraints as product-inherent constraints. Not violating these time constraints is essential to avoid scrap and similarly increase quality-based yield. To that end, transition times are forecasted and the adherence to these product-inherent constraints is evaluated based on one-sided prediction intervals and point estimators. The inclusion of product-inherent constraints leads to significant adherence improvements in the production system as indicated in the real-world semiconductor manufacturing case study and, hence, contributes a novel, data driven approach for production control. As a conclusion, the ability to avoid a large majority of violations of time constraints shows the approaches effectiveness and the future requirement to more accurately integrate such product-inherent constraints into production control.

Keywords: Complex job shop; Time constraint; Semiconductor manufacturing; Production control (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10845-024-02472-6

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