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.
Highlights
The production of a product may be completed using the raw material obtained from different phases of production processes
It can be noted that the proposed sampling plan provides the lot acceptance probability in the indeterminate interval while the existing plan under classical statistics provides the determined values of lot acceptance probability
CONCLUDING REMARKS We proposed one of the simplest acceptance sampling plans namely, single sampling plan for inspecting the quality of the raw materials where the quality characteristic follows inflated Pareto distribution under the neutrosophic statistics (NS)
Summary
The production of a product may be completed using the raw material obtained from different phases of production processes. According to the results of presence/absence, the sample items are classified as either conforming or non-conforming in attribute quality characteristic inspection whereas, the measurements of the quality characteristic are considered in variables inspection Both sampling plans are frequently used to make a decision on the disposition of the batch. In order to overcome the drawback of assumptions of distribution, the measurements of the quality characteristic are estimated from the history of the production process The applications of both attribute and variables sampling plans can be found in many fields including the food industry. It is important to mention that a number of authors studied the designing of control chart as well as sampling plans for both attribute and variables inspection under various zero-inflated distributions. We expect that the proposed sampling plan will be more flexible, adequate and effective under indeterminacy situations
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