Open Access

ARTICLE

Efficient Process Monitoring Under General Weibull Distribution

Saman Hanif Shahbaz, Muhammad Qaiser Shahbaz^*

Department of Statistics, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia

* Corresponding Author: Muhammad Qaiser Shahbaz. Email:

(This article belongs to the Special Issue: Data Analytics in Industry 4.0)

Computer Systems Science and Engineering 2022, 40(1), 287-297. https://doi.org/10.32604/csse.2022.018219

Received 01 March 2021; Accepted 29 April 2021; Issue published 26 August 2021

Abstract

Product testing is a key ingredient in maintaining the quality of a production process. The production process is considered an efficient process if it is capable of quick identification of faulty products. The items produced by any production process are usually packed and acceptance or rejection of the pack depends upon its conformity to some specified quality level. Generally, the specified quality level is based upon the number of defective items found in the inspected number of items. Such decisions are based upon some rules and usually acceptance of the pack is based upon a fewer number of defective items in the pack. Such questions can be answered by using acceptance sampling plans. The acceptance sampling plans assume the fact that the quality level of the item follows some probability distribution. The sampling plans based upon some classical probability distributions are available but often it happens that the quality behavior of the product does not follow a simple probability model and hence the available sampling plans fail. In this paper, we have developed acceptance sampling plans when the product life follows a general Weibull distribution. The sampling plans have been constructed by considering the crisp and fuzzy behavior of the acceptance probability. These sampling plans have been constructed by assuming an infinite lot size. It has been found that the number of items required for inspection decreases with an increase in some parameters.

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Keywords

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