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Erschienen in:

2024 | OriginalPaper | Buchkapitel

Solving an Intelligent Scheduling Problem in an Automobile Factory

verfasst von : Tsui-Ping Chung, Meng Qiu

Erschienen in: Proceedings of Industrial Engineering and Management

Verlag: Springer Nature Singapore

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Abstract

The research on intelligent manufacturing is divided into two parts, namely equipment intelligence and decision-making system intelligence. In the process of promoting intelligent manufacturing, it is not only necessary to automate the transformation of equipment and systems, but also to make their systems possess the characteristics of intelligent decision-making. One of scheduling problem inspired by a real case from the automobile factory with undergoing digital transformation is considered and a mathematical model is established to solve this scheduling problem. A simple heuristic is proposed to solve the problem. The solution is better than that by current method.

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Vorheriges Kapitel Intelligent Cooperation by Solving a Two-Stage Production Assembly Scheduling Problem with a Heuristic Algorithm in Canned Food Plant

Nächstes Kapitel Research on Mixed-Model Assembly Line Rebalancing Considering Skill Differences and Series–Parallel Design

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Guo Y, Guo T, Wei D (2021) Multi-layered coding-based study on optimization algorithms for automobile production logistics scheduling. Technol Forecast Soc Change 170. https://doi.org/10.1016/j.techfore.2021.120889

Yao X, Almatooq N, Askin RG, Gruber G (2022) Capacity planning and production scheduling integration: improving operational efficiency via detailed modelling. Int J Prod Res 60(24):7239–7261CrossRef

Staeblein T, Aoki K (2015) Planning and scheduling in the automotive industry: a comparison of industrial practice at German and Japanese makers. Int J Prod Econ 162:258–272CrossRef

Lu C, Gao L, Yi J, Li X (2021) Energy-efficient scheduling of distributed flow shop with heterogeneous factories: a real-world case from automobile industry in China. IEEE Trans Industr Inf 17(10):6687–6696CrossRef

Lewandowski R, Olszewska JI (2020) Automated task scheduling for automotive industry. In: 2020 IEEE 24th international conference on intelligent engineering systems (INES). https://doi.org/10.1109/INES49302.2020.9147169

Jin W, He Z, Peng T (2021) A JIT part supply scheduling strategy with electric transport device between central receiving store and supermarkets in the automobile industry considering energy. eTransportation 9. https://doi.org/10.1016/j.etran.2021.100126

Zhou B, Zhao Z (2022) A hybrid fuzzy-neural-based dynamic scheduling method for part feeding of mixed-model assembly lines. Comput Industr Eng 163. https://doi.org/10.1016/j.cie.2021.107794

Titel: Solving an Intelligent Scheduling Problem in an Automobile Factory
verfasst von: Tsui-Ping Chung
Meng Qiu
Verlag: Springer Nature Singapore
Buch: Proceedings of Industrial Engineering and Management
Print ISBN: 978-981-9701-93-3

Electronic ISBN: 978-981-9701-94-0

Copyright-Jahr: 2024
DOI: https://doi.org/10.1007/978-981-97-0194-0_14

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