Plan for Food Inspection for Inflated-Pareto Data under Uncertainty Environment

Abstract

The existing sampling plans for food inspection have been designed under classical statistics. These sampling plans are applied in the food industry under the assumption that all observations are determined, clear and certain. The neutrosophic statistics (NS) which is the generalization of classical statistics applied under uncertainty environment. In this paper, we propose one of the simplest acceptance sampling plans namely, a single sampling plan for inspecting the quality of the raw materials where the quality characteristic follows inflated Pareto distribution under the NS. The neutrosophic plan parameters are determined under the neutrosophic statistical interval method (NISM). We provide the range/interval of the sample sizes and acceptance criteria which satisfy both producer and consumer expectations. The advantages of the proposed plan are given. An example from the food industry is selected to explain the proposed plan.