This paper reports a literature review on the Artificial Intelligence (AI) techniques applied in the field of production planning and scheduling and explores the synergistic integration of AI with simulation for enhancing production scheduling. Leveraging Microsoft Project Bonsai and AnyLogic, we present a case study that demonstrates the effectiveness of AI-driven simulation models in optimizing scheduling tasks. Our research highlights the potential of combining AI with traditional simulation methods. The results offer insights into the practical applications and future potential of AI in industrial automation and production management.

COMBINED USE OF AI TECHNIQUES AND SIMULATION TO SUPPORT PRODUCTION SCHEDULING: EVIDENCE FROM EMPIRICAL RESEARCH / Bandinelli R.; Fani V.. - STAMPA. - 38:(2024), pp. 34-40. (Intervento presentato al convegno 38th ECMS International Conference on Modelling and Simulation, ECMS 2024 tenutosi a pol nel 2024).

COMBINED USE OF AI TECHNIQUES AND SIMULATION TO SUPPORT PRODUCTION SCHEDULING: EVIDENCE FROM EMPIRICAL RESEARCH

Bandinelli R.
;
Fani V.
2024

Abstract

This paper reports a literature review on the Artificial Intelligence (AI) techniques applied in the field of production planning and scheduling and explores the synergistic integration of AI with simulation for enhancing production scheduling. Leveraging Microsoft Project Bonsai and AnyLogic, we present a case study that demonstrates the effectiveness of AI-driven simulation models in optimizing scheduling tasks. Our research highlights the potential of combining AI with traditional simulation methods. The results offer insights into the practical applications and future potential of AI in industrial automation and production management.
2024
Proceedings - European Council for Modelling and Simulation, ECMS
38th ECMS International Conference on Modelling and Simulation, ECMS 2024
pol
2024
Bandinelli R.; Fani V.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1399620
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