Author(s)

ZeBin Wang¹, SaiNan He¹, YuDong Zhao¹, ZhengBo Li^2*

Affiliation(s)

¹Department of Automation for Brewing Engineering, MouTai Institute, Ren Huai 564500, GuiZhou, China.

²Department of Public Basic Education, MouTai Institute, Ren Huai 564500, GuiZhou, China.

Corresponding Author

ZhengBo Li

ABSTRACT

This study proposes an optimization method for production decisions in the manufacturing process of popular electronic products, focusing on issues such as component procurement, product assembly, and quality inspection. In the production process, companies need to purchase key components, and any defective part may lead to a substandard final product. For defective products, the company may choose to either scrap or disassemble them for recycling. This paper employs a binomial distribution model to design a sampling inspection scheme, establishes a mathematical model, and determines the sample size at different confidence levels to accurately assess whether the defect rate exceeds the threshold. Additionally, this paper integrates various factors to construct a production cost minimization model, identifying the optimal production strategy in most scenarios. This strategy includes comprehensive inspections of both components and finished products, as well as disassembly and recycling plans for defective products. The results show that optimizing production decisions can significantly improve production efficiency, reduce costs, and enhance the company’s market competitiveness.

KEYWORDS

Binomial distribution model; Production cost minimization; Multi-stage decision optimization; Production process efficiency

CITE THIS PAPER

ZeBin Wang, SaiNan He, YuDong Zhao, ZhengBo Li. Decision optimization in the production process based on dynamic programming. Trends in Social Sciences and Humanities Research. 2025, 3(3): 24-31. DOI: https://doi.org/10.61784/tsshr3148.

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