Design of single and double acceptance sampling plans based on neutrosophic sets

2021 ◽  
pp. 1-18
Author(s):  
Gürkan Işik ◽  
İhsan Kaya
Keyword(s):  
Fuzzy Set ◽  
Acceptance Sampling ◽  
Good Representation ◽  
Neutrosophic Sets ◽  
Defective Items ◽  
Sample Number ◽  
Sampling Plans ◽  
Acceptance Sampling Plans ◽  
Different Sources ◽  
Average Sample

Although traditional acceptance sampling plans (ASPs) need certain mass quality characteristics, it is not easy to define them as crisp value in some real case problems. The fuzzy set theory (FST) is one of the popular techniques to model uncertainties of the process and therefore fuzzy ASPs have been offered in the literature. Fuzzy set extensions have been proposed recently for better modeling of the uncertainties having different sources and characteristics. One of these extensions named neutrosophic sets (NSs) can be used to increase the sensitiveness and flexibility of ASPs. The ASPs based on NSs can give ability to classify the items as defective, non-defective and indeterminate. Since the operator can become indecisive for slightly defective items, these plans can provide a good representation of human evaluations under uncertainty. In this study, single and double ASPs are designed based on NSs by using binomial and poisson distributions that are also re-analyzed based on NSs. For this aim, some characteristics functions of ASPs such as probability of accepting a lot (Pa), average outgoing quality (AOQ), average total inspection (ATI) and average sample number (ASN) have also been analyzed based on NSs. Numerical examples are presented to analyze the proposed plans.

scholarly journals Mixed Variables-Attributes Test Plans for Single and Double Acceptance Sampling under Exponential Distribution

2011 ◽  
Vol 2011 ◽  
pp. 1-15 ◽  
Author(s):  
Yan Li ◽  
Xiaolong Pu ◽  
Dongdong Xiang
Keyword(s):  
Exponential Distribution ◽  
Operating Characteristic ◽  
Acceptance Sampling ◽  
Sample Sizes ◽  
Sample Number ◽  
Sampling Plans ◽  
Average Sample Number ◽  
Mixed Variables ◽  
Average Sample

The mixed variables-attributes test plans for single acceptance sampling are proposed to protect “good lots” from attributes aspect and to optimize sample sizes from variables aspect. For the single and double mixed plans, exact formulas of the operating characteristic and average sample number are developed for the exponential distribution. Numerical illustrations show that the mixed sampling plans have some advantages over the variables plans or attributes plans alone.

Design of single and double acceptance sampling plans based on interval type-2 fuzzy sets

2021 ◽  
pp. 1-13
Author(s):  
Gürkan Işık ◽  
İhsan Kaya
Keyword(s):  
Fuzzy Sets ◽  
Fuzzy Set ◽  
Measurement Errors ◽  
Uncertainty Modeling ◽  
Characteristic Functions ◽  
Acceptance Sampling ◽  
Sampling Plans ◽  
Acceptance Sampling Plans ◽  
Interval Type

Defectiveness of items is generally considered as a certain value in acceptance sampling plans (ASPs). It is clear that, it may not be certainly known in some real-case problems. Uncertainties of the inspection process such as measurement errors, inspectors’ hesitancies or vagueness of the process etc. should be taken into account to obtain more reliable results. The fuzzy set theory (FST) is one of the best methods to overcome these problems. There are some studies in the literature formulating the ASPs with the help of FST. Deciding the right membership functions of the fuzzy sets (FSs) has a vital importance on the quality of the uncertainty modeling. Additionally, the fuzzy set extensions have been offered to model more complicated uncertainties to achieve better modeling. As one of these extensions, type-2 fuzzy sets (T2FSs) gives an ability to model uncertainty in situations where it is not possible to determine exact membership function parameters. In this study, single and double ASPs based on interval T2FSs (IT2FSs) have been designed for binomial and Poisson distributions. Thus, it becomes possible to make more flexible, sensitive and descriptive sensitivity analyzes. The main characteristic functions of ASPs have been derived and the suggested formulations have been illustrated on a comparative application from manufacturing process. Results allowing for more comprehensive analysis as against to the traditional and T1FSs based plans have been obtained.

scholarly journals Design of Fuzzy Sampling Plan Using the Birnbaum-Saunders Distribution

Mathematics ◽  
2018 ◽  
Vol 7 (1) ◽  
pp. 9 ◽  
Author(s):  
Muhammad Zahir Khan ◽  
Muhammad Farid Khan ◽  
Muhammad Aslam ◽  
Abdur Razzaque Mughal
Keyword(s):  
Operating Characteristic ◽  
Real Life ◽  
Sampling Plan ◽  
Acceptance Sampling ◽  
Acceptance Probability ◽  
Defective Items ◽  
Sampling Plans ◽  
Fuzzy Environment ◽  
Acceptance Sampling Plan ◽  
Acceptance Sampling Plans

Acceptance sampling is one of the essential areas of quality control. In a conventional environment, probability theory is used to study acceptance sampling plans. In some situations, it is not possible to apply conventional techniques due to vagueness in the values emerging from the complexities of processor measurement methods. There are two types of acceptance sampling plans: attribute and variable. One of the important elements in attribute acceptance sampling is the proportion of defective items. In some situations, this proportion is not a precise value, but vague. In this case, it is suitable to apply flexible techniques to study the fuzzy proportion. Fuzzy set theory is used to investigate such concepts. It is observed there is no research available to apply Birnbaum-Saunders distribution in fuzzy acceptance sampling. In this article, it is assumed that the proportion of defective items is fuzzy and follows the Birnbaum-Saunders distribution. A single acceptance sampling plan, based on binomial distribution, is used to design the fuzzy operating characteristic (FOC) curve. Results are illustrated with examples. One real-life example is also presented in the article. The results show the behavior of curves with different combinations of parameters of Birnbaum-Saunders distribution. The novelty of this study is to use the probability distribution function of Birnbaum-Saunders distribution as a proportion of defective items and find the acceptance probability in a fuzzy environment. This is an application of Birnbaum-Saunders distribution in fuzzy acceptance sampling.

New Acceptance Sampling Plans Based on Percentiles for Exponentiated Fréchet Distribution

2016 ◽  
Vol 31 (1) ◽  
Author(s):  
Gadde Srinivasa Rao ◽  
Kanaparthi Rosaiah ◽  
Mothukuri Sridhar Babu ◽  
Devireddy Charanaudaya Sivakumar
Keyword(s):  
Operating Characteristic ◽  
Real Data ◽  
Acceptance Sampling ◽  
Producer’S Risk ◽  
Data Set ◽  
Sampling Plans ◽  
Fréchet Distribution ◽  
Acceptance Sampling Plans ◽  
Characteristic Values ◽  
Frechet Distribution

AbstractIn this article, acceptance sampling plans are developed for the exponentiated Fréchet distribution based on percentiles when the life test is truncated at a pre-specified time. The minimum sample size necessary to ensure the specified life percentile is obtained under a given customer's risk and producer's risk simultaneously. The operating characteristic values of the sampling plans are presented. One example with real data set is also given as an illustration.

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