Statistical model-based optimisation problem for production decision-making
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DOI: 10.25236/icetmr.2024.004
Corresponding Author
Yulin Li
Abstract
With the rapid development of the electronic products market, quality control and cost optimisation in the production process have become the core issues of concern for enterprises. This paper establishes a series of mathematical models for the decision-making problems faced by an enterprise in the production process, such as the procurement of spare parts, assembly and the treatment of defective products, in order to achieve the minimisation of production costs and the maximisation of profits. Firstly, the sampling test method is used to determine whether the defective rate of spare parts exceeds the nominal value under a certain level of confidence, so as to decide whether to accept this batch of spare parts or not. This paper assumes that the defective rate of spare parts follows the binomial step, and also assumes that the number of defective parts in the sample is approximately normally distributed, and carries out the design of the sampling scheme. The sampling scheme is designed to help enterprises make decisions at various stages of the production process, including the inspection of spare parts and finished products, and the treatment of substandard products. In this paper, a violent search algorithm is used to traverse all the decision combinations, determine the optimal inspection and disassembly decisions in each case, and adjust the strategies according to different defective rates and cost parameters, and finally arrive at the strategy with the largest net profit.
Keywords
Statistical Modelling, Production Decision Making, Sampling and Testing, Optimisation Models