摘要
In the supply chain context, buyers and suppliers typically employ sampling inspection to assure product quality, safeguarding mutual interests. Practitioners formulate acceptance sampling plans to implement sampling inspections efficiently. With the continuous advancement of sampling techniques, the quick-switch sampling system (QSS), known for its dynamic decision-rule transformation mechanism and cost-effectiveness, has garnered extensive discussion. However, the existing rule transformation mechanism in QSS is flawed because it requires only a single acceptance to switch back to normal inspection after a lot is rejected. From a managerial perspective, when a supplier lot is rejected, it suggests possible quality concerns. Practitioners may prefer multiple acceptances in tightened inspections of subsequent lots to affirm the reliability of the supplier's process capability. This study applied the Markov chain theory to construct a generalised dual sampling system (GDSS) with a flexible decision-rule transformation mechanism to address these limitations in the current QSS. The GDSS allows practitioners to specify the number of consecutive lot acceptances required for transitioning from a tightened back to a normal inspection, rendering the inspection process more rigorous and flexible. Following a series of investigations and performance comparisons, the developed GDSS is more cost-effective than the existing QSS. Furthermore, the GDSS enhances the sensitivity in detecting quality degradation in delivery lots, offering greater advantages and flexibility for buyers and suppliers. Finally, we demonstrate and validate the applicability of the proposed methodology through a practical case study.