Abstract
Supplier-buyer relationships have been the focus of considerable supply chain management and marketing research for decades. To validate the process capability of a supplier, practitioners usually operate the acceptance sampling plan (ASP). The most basic ASP is a single sampling plan (SSP) due to its straightforward lot-disposition mechanism. However, since the lot-disposition mechanism of SSP cannot accommodate the historical lot-quality levels information, it requires a large sample size for inspection to validate the submitted lot's process capability. To obtain these benefits from historical information, multiple-lot dependent state (MDS) sampling plans have been proposed. The MDS plans have manufacturing traceability of historical lot-quality levels information to sentence the submitted lot. However, the MDS plan's manufacturing traceability has a drawback that cost-efficiency decreases as more historical lot-quality levels information are considered, which contradicts its initial development goal. To overturn this contradictory situation, we proposed the adaptive MDS (AMDS) plans based on the process loss restricted consideration with combinatorial mathematical treatment that can correct the MDS plans manufacturing traceability of historical lot-quality levels information that help practitioners to adopt more historical information into lot-disposition freely without bearing the reduction of cost-efficiency. Meanwhile, their performances are superior to existing MDS plans in terms of cost-effectiveness and discriminatory power. Moreover, we further developed a web-based app for our proposed plans to improve the convenience of applying them in practice. By operating the web-based app, practitioners can quickly obtain the optimal plan criteria without bearing the burdens of table-checking or mathematical model solving. These improvements can genuinely help buyers distinguish reliable suppliers efficiently and build up a strong partnership with them. Finally, the applicability of the proposed plan is demonstrated in a real-world case study.
Highlights
Supplier-buyer relationships have been the considerable focus of supply chain management and marketing research for decades [1,2]
In practice, the manufacturing traceability of multiple-lot dependent state (MDS) plans has been limited. To tackle this contradictory situation, we proposed an adaptive MDS (AMDS) plan based on the bilateral qualitycharacteristic capability index with the process loss restricted
The Le -MDS plan was developed by Aslam et al [25]
Summary
Supplier-buyer relationships have been the considerable focus of supply chain management and marketing research for decades [1,2]. When more historical lot-quality levels information is considered by practitioners, we discover the MDS plans’ required sample size for inspection presents an upward trend, and the lot-accepted criterion shows a downward trend. This outcome indicates the MDS plans’ cost-efficiency and discrimination power will decrease as more historical lot-quality levels of information are considered, which contradicts the initial goal of the development of MDS plans. This contradiction may become serious for the long-term supplier-buyer relationship since it has numerous traceable deliveries and lot-disposition operations. By operating the user interface of our proposed web-based app, practitioners can quickly obtain the optimal plan criteria without bearing table-checking or mathematical-model solving burdens
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