小批量多返工生产系统瞬态性能分析和优化

Translated title of the contribution: Transient performance analysis and optimization of multi-rework production systems with small-lot order

Zhi Yang Jia*, Ze Jun Ni, Zun Jun Wang, Gang Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

With the introduction of smart manufacturing and green manufacturing strategies, the demand for small batch customized production is increasing in actual production. Moreover, rework production lines are being used more frequently in actual production in order to further improve the processing efficiency and product quality. Based on the context of small batch production, the transient performance of a multi-rework system with unreliable machines and finite buffers is analysed. Meanwhile, the production scheduling of the multi-rework system is carried out. To quantitatively analyse the transient performance of this production system, a mathematical model of the system is established using the Markov analysis method. Besides, a dynamic decomposition and aggregation algorithm is proposed to predict the transient performance indicators such as productivity, consumption rate and work-in-process inventory of the system, and the accuracy and effectiveness of the proposed algorithm are verified based on simulation comparison experiments. In addition, a genetic algorithm is used to optimize the production performance of the system for a labour-constrained scenario with a reasonable allocation of the efficiency of each machine. Finally, the allocation strategy concluded from the experimental results of labour allocation provides decision support for the production operation of the system.

Translated title of the contributionTransient performance analysis and optimization of multi-rework production systems with small-lot order
Original languageChinese (Traditional)
Pages (from-to)2746-2754
Number of pages9
JournalKongzhi yu Juece/Control and Decision
Volume39
Issue number8
DOIs
Publication statusPublished - Aug 2024

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