A Sampling-Based Inspection and Cost Optimization Model for Electronic Assembly Quality Control

In electronic assembly, inspection is worthwhile only when the cost of testing is justified by the losses avoided by preventing defective products from reaching customers. This study examines that balance by developing a mathematical model that integrates one-sided acceptance sampling with an expected-cost framework covering component inspection, finished-product inspection, exchange loss, and the disassembly of defective products. The analysis is first developed for a two-component assembly case and then extended to a multi-stage, multi-component process. Because defect rates are often estimated from limited samples rather than known in advance, interval-based parameter correction is introduced and compared with an electrical-test dataset of 80,000 cleaned records from 866 lots. The data give a final-product defective rate of 1.335%, with a 95% confidence interval of 1.255–1.415%, which is well below the nominal 10% rate used in the baseline scenarios. Nevertheless, the distribution across stable lots shows a pronounced right tail, indicating that some lots remain riskier than the average level suggests. Routine full inspection of finished products is therefore difficult to justify at low average defect rates, whereas higher exchange losses or upper-tail lots can make tighter inspection economically reasonable. The model provides a practical route from sampling evidence to inspection and cost-control decisions in electronic assembly.