Optimal Decision-Making Model for Multi-Process and Multi-Component Production in Enterprises_Vol. 3 No. 3 (JIEM 2025)_Journal of Industry and Engineering Management (ISSN: 2959-0612)

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Optimal Decision-Making Model for Multi-Process and Multi-Component Production in Enterprises

DOI: https://doi.org/10.62517/jiem.202503304

Author(s)

Dongxue Tu1,2,*, Baiqi Zhang3, Cuirong Lu3, Yixing Zhu3

Affiliation(s)

1Department of Basic Course Teaching and Research, Guangdong Technology College, Zhaoqing, Guangdong, China 2Faculty of Arts, Communication & Education, Centre for Postgraduate Studies (CPS), Kuala Lumpur University of Science and Technology, Selangor, Kuala Lumpur, Malaysia 3School of Information, Guangdong Technology College, Zhaoqing, Guangdong, China * Corresponding Author

Abstract

To optimize the cost structure of enterprises, improve decision-making in the production process, and enhance production and quality control decisions, this study comprehensively considers factors such as the procurement cost of finished products, inspection costs, replacement losses, disassembly, and assembly costs. By employing statistical inference, hypothesis testing, genetic algorithms, dynamic programming, and other methods, along with collected data and materials, a three-stage multi-process, multi-component production optimization decision-making model is established, covering component inspection, finished product inspection, and defective product disassembly. A sampling inspection model was implemented using Python programming, enabling enterprises to effectively control component quality. This model provides the optimal decision-making solution for the production process.

Keywords

Optimal Decision-Making Model; Hypothesis Testing; Dynamic Programming; Sampling Inspection Model; Component Quality Control

References

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