Research on Decision Optimization and Sampling Inspection Schemes in the Production Process

Abstract

In the production process, decision-making problems usually involve multiple stages, and the decision-making of each stage often affects the efficiency, cost and profit of the whole production chain. This article mainly studies the decision-making of the production process. For samples with a nominal substandard rate of 10%, small and large samples were analyzed by sequential sampling, and the results were tested using the ASN efficiency index. The acceptance rate and rejection rate obtained were inferred whether this batch of spare parts was accepted. During the production process, 10,000 pieces of data are randomly generated for decisions that require parts inspection and simulated under different circumstances. Take 80% of the 10,000 data as a training set and 20% as a test set, calculate the expectations of each decision point, and find out the best procurement and production strategies, so as to derive the optimal method. For m processes, n spare parts, divide the problems into sub-problems, use dynamic planning to gradually find out the optimal decision-making of each problem, and use the DP matrix to solve the optimal result. This method can not only effectively reduce the number of sampling tests and reduce the cost of testing, but also optimize the production process through dynamic planning and improve the efficiency of resource utilization. The research results provide enterprises with operable theoretical basis and practical guidance, which helps enterprises to reduce costs and increase efficiency in the fierce market competition and improve overall economic benefits.