Cost optimization of acceptance sampling plan in a fuzzy supply chain environment

Abstract

PurposeThe purpose of the paper is set to minimize the total cost of a manufacturing system when an acceptance sampling plan (ASP) is carried out in a fuzzy environment.Design/methodology/approachA fuzzy acceptance sampling plan (FASP) is employed for the inspection of the batch of products and a fuzzy cost optimization problem is formulated.FindingsThe extent of uncertainty determines an interval for the total cost function with upper and lower bounds. The effect of variation in the ambiguity of the proportion of defectives in the probability of acceptance is determined.Practical implicationsThe proposed model is specifically designed for production and supply units with ASP for attributes. Still, the proportion of defectives in the inspection process is fuzzy.Originality/valueFuzzy probability distribution is used to model an optimal inspection plan for a general supply chain. Economic design of supply chain under fuzzy proportion of defectives is discussed for the first time.