Quality Inspection of Electronic Product Assembly Line Components and Multi-Stage Decision Optimization Model in Flexible Manufacturing Systems Based on SPRT and Intelligent Algorithms

Abstract

Flexible manufacturing systems (FMS) demand intelligent and adaptive quality control mechanisms to handle the challenges of high product variability and small batch production. This paper proposes an integrated decision-making framework combining sequential probability ratio test (SPRT), Bayesian update, Monte Carlo simulation, and genetic algorithm to address uncertainty in inspection and production optimization. We develop dynamic sampling models to reduce inspection cost, update defect rate estimates in real time using Bayesian inference, and employ intelligent search to optimize inspection, assembly, and disassembly decisions. Experiments on a simulated electronic product assembly line demonstrate that our approach outperforms traditional methods by reducing average inspection size, increasing decision reliability, and improving overall profit.