An integrated supply chain model with errors in quality inspection and learning in production

It is imperative for contemporary businesses to proactively search for ways of continuously improving the performance of their supply chains. Supply chain coordination and integrated decision making across the supply chain among various supply chain partners are frequently employed towards this end. Such supply chain coordination strategies include the use of common cycle time, quantity discounts, optimal lot sizing, quality improvements and inspections, etc. An important issue lacking in the supply chain literature relates to the incorporation of such quintessential and omnipresent human factors as errors in quality inspections and production improvements due to learning. This paper provides a simple but integrated mathematical model for determining an optimal vendor–buyer inventory policy by accounting for quality inspection errors at the buyer’s end and learning in production at the vendor’s end. The objective is to minimize the joint annual cost incurred in the supply chain. A numerical example is presented to illustrate the application and the substance of the proposed model. We discuss how such integrated models can be used for justifying investments in such strategic and operational areas as relationship management, product design, process design, and personnel training. We also provide some very interesting and challenging future research directions.

► Used a conventional stocking policy to study a vendor–buyer supply chain.
► Incorporated two important human factors to a model in the literature.
► Learning in production brought in a substantial drop in the annual cost of the supply chain.
► Type I error has a more pronounced effect on the supply chain costs as compared to the Type II errors.
► This model can be used for justifying investments in relationship management, product/process design and workers’ training.