Sequential Sampling Inspection Study of Electronic Product Parts Based on the Monte Carlo Model

Abstract

With the rapid development of the electronic product market and the increasingly diverse consumer demands, quality control in the procurement of parts, assembly, and sale of electronic products has become critically important for enterprises. This paper aims to establish a mathematical model to explore how to effectively reduce inspection costs, improve production efficiency, and ultimately achieve profit maximization. Targeting defective rates in parts, this study considers the randomness of sampling and actual product quality, adopting sequential sampling inspection as the testing method. Using the Monte Carlo model, it simulates expected sample values for defective rates between 11% and 50% under varying confidence levels. Likelihood ratios of the expected sample values are calculated and compared, enabling the development of decision criteria for accepting or rejecting a batch of parts. The results demonstrate that the sequential sampling inspection method can effectively reduce inspection frequency and costs while maintaining accuracy, providing an efficient quality control approach for enterprises.