Generalized Multiple Dependent State Sampling Plans in Presence of Measurement Data

Ritwik Bhattacharya,Muhammad Aslam

doi:10.1109/access.2020.3021504

Abstract

This article introduces a generalized version of the multiple dependent state sampling plan based on the measurement data, that is, when the quality characteristic is measured in a numerical scale. The conditions of application and the operating procedures of the proposed plan are discussed sequentially. A few important performance measures, such as operating characteristic curve, average total inspection and average sample number, are developed. The advantage of the proposed plan over the multiple dependent state sampling and single sampling plan is demonstrated through numerical example. Finally, one real-life data set is analyzed to illustrate the application of the proposed sampling plan.

Highlights

Testing and inspection of the finished products are done to see either the manufactured product meets the given specifications or not
The variable sampling plan is applied when the quality characteristic under consideration is measured in a numerical scale
Variable sampling plan has an advantage over attribute sampling plan in the sense that same operating characteristic curve can be obtained

Summary

Introduction

Testing and inspection of the finished products are done to see either the manufactured product meets the given specifications or not. This type of activity alerts the producer to enhance the quality of the product. A lot of the products is accepted if the experimenter found the items in the sample are according to given specifications, otherwise, the lot of the products will be rejected. The variable sampling plan is applied when the quality characteristic under consideration is measured in a numerical scale. This situation is occurred when the quality characteristic follows a probability distribution. Variable sampling plan has an advantage over attribute sampling plan in the sense that same operating characteristic curve can be obtained

Objectives

Results

Conclusion