An efficient partial sampling inspection for lot sentencing based on process yield

As the process yield has significantly raised because of the advanced development of manufacturing technology today, engineers would logically attempt to inspect fewer sample items for the quality evaluation of processes or products. Therefore, in this paper, an efficient sampling inspection method based on the process yield index Spk is developed for lot sentencing, wherein the inspection is performed only on a fractional submitted lot rather than examining every following submission. Both the average sample number (ASN) and operating characteristic (OC) functions of the proposed method are derived on the basis of the Markov chain technique. Further, an optimization model that minimizes the ASN and constrains two OC functions restricted to given quality requirements and tolerable risks is constructed. Performance comparisons in terms of economy and discriminatory power are analyzed by contrasting ASN and OC curves with existing Spk-based methods under the same quality conditions to emphasize the superiority of the proposed method. For easy implementation, we prove the applicability of the proposed method by demonstrating a case study taken from an integrated circuit packaging company.