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2022 | OriginalPaper | Buchkapitel

Integrated Simulation-Based Optimization Approach for Production Scheduling: A Use Case Application in a Machining Process

verfasst von : Ícaro Romolo Sousa Agostino, Mauricio Randolfo Flores da Silva, Enzo Morosini Frazzon, Luciana Amaral Stradioto Neto

Erschienen in: Dynamics in Logistics

Verlag: Springer International Publishing

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Abstract

The scheduling of complex manufacturing systems requires the integration of production, inventory, and maintenance to obtain a robustness control and performance. In this context, this paper proposes a data-driven simulation-based optimization approach for production scheduling to optimize job shop sequencing decisions considering inventory availability and machine breakdowns. The approach consists in the implementation of a combination of genetic algorithm with discrete-event simulation model aiming to optimize the selection sets of dispatching rules for groups of machines in the job shop to improve the manufacturing system performance. The approach was evaluated in a machining process, part of a job system of a Brazilian industry of the dental and medical sector, achieving better performance for the average lead time with the improvement of 10.27% compared to the current strategy of the company.

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Vorheriges Kapitel Dynamic Lot Size Optimization with Reinforcement Learning

Nächstes Kapitel Scheduling Workforce in Decentrally Controlled Production Systems: A Literature Review

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Titel: Integrated Simulation-Based Optimization Approach for Production Scheduling: A Use Case Application in a Machining Process
verfasst von: Ícaro Romolo Sousa Agostino
Mauricio Randolfo Flores da Silva
Enzo Morosini Frazzon
Luciana Amaral Stradioto Neto
Verlag: Springer International Publishing
Buch: Dynamics in Logistics
Print ISBN: 978-3-031-05358-0

Electronic ISBN: 978-3-031-05359-7

Copyright-Jahr: 2022
DOI: https://doi.org/10.1007/978-3-031-05359-7_31

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