Acceptance Sampling Plans for Finite and Infinite Lot Size under Power Lindley Distribution

Shahbaz, Saman Hanif; Khan, Khushnoor; Shahbaz, Muhammad

doi:10.3390/sym10100496

Cited by 10 publications

(10 citation statements)

References 8 publications

(12 reference statements)

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“…The plan parameters are computed by using the fuzzy inequalities given in Eqs. (10) and (11). In the case of a fuzzy sampling plan, the plan parameters are pair of values n L ; c L ð Þand n H ; c H ð Þ.…”

Section: Fuzzy Sampling Plans Under General Weibull Distributionmentioning

confidence: 99%

“…The sampling plan under progressive type I censoring for Weibull distribution has been discussed by Ding et al [9], among others. The sampling plan for power Lindley distribution, introduced by Ghitany et al [10], has been proposed by Hanif Shahbaz et al [11]. The study of acceptance sampling plans is ever increasing and in this paper we have discussed the acceptance sampling plans when the life length of the product follows the Topp-Leone weighted Weibull distribution, proposed by Abbas et al [12].…”

Section: Introductionmentioning

confidence: 99%

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Efficient Process Monitoring Under General Weibull Distribution

Shahbaz¹,

Shahbaz²

2022

Computer Systems Science and Engineering

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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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Section: Fuzzy Sampling Plans Under General Weibull Distributionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Efficient Process Monitoring Under General Weibull Distribution

Shahbaz¹,

Shahbaz²

2022

Computer Systems Science and Engineering

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“…For a given value of producer's risk, say u = 0:05, the researcher is concerned in determining the value of m=m 0 that asserts the producer risk will not exceed u. The value of m=m 0 is the minimum positive number for which p = F t m 0 m 0 m satisfies the inequality For a given ASP n, c, t=m 0 ð Þunder the TPQSD at an identified confidence level P * , the smallest values of m=m 0 , satisfying (14), are presented in Table 3 for F TPQSD (x; u = 3, a = 2) and in Table 5 for F TPQSD (x; u = 2, a = 3).…”

Section: Producer's Riskmentioning

confidence: 99%

“…For a given ASP n, c, t=m 0 ð Þunder the TPQSD at an identified confidence level P * , the smallest values of m=m 0 , satisfying (14), are presented in Table 3 for F TPQSD (x; u = 3, a = 2) and in Table 5 for F TPQSD (x; u = 2, a = 3).…”

Section: Producer's Riskmentioning

confidence: 99%

Acceptance sampling plans under two-parameter Quasi Shanker distribution assuring mean life with an application to manufacturing data

2021

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The acceptance sampling plan (ASP) is a statistical tool used in industry for quality control to determine the quality of products by selecting a specified number for testing in order to accept or reject the lot. The main objective is to develop a new ASP based on truncated life tests assuming that the lifetime follows the two parameters Quasi Shanker distribution, since this distribution showed its superiority in providing a better model for some applications than the exponential distribution. The ASP steps are carried out to find the minimum sample sizes needed to assert the certain life mean that are calculated under a given customer’s risk. The operating characteristic values of the sampling plan and the producer risk values are obtained. The efficiency of the suggested plans is analyzed based on real data that is fitted to the Quasi Shanker distribution. For various values of the Quasi Shanker distribution parameters, numerical examples are presented for illustrative purposes. The results indicate that the suggested ASP provides smaller sample sizes than other competitors considered in this study. The suggested ASP has been found to provide a substantial sampling economy in terms of reducing the sample. Hence, it is recommended that the ASP can be used in industry and for future research works as double and group ASP.

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“…Chowdhury [12] designs an acceptance sampling plan under a truncated lifetime test at the pre-assigned time for generalized Weibull distribution and finds the smallest sample size for the median life of the experimental unit. Shahbaz et al [13] propose single and double acceptance sampling plans for the power Lindley distribution by considering finite and infinite lot sizes. Al-Omari et al [14] develop an acceptance sampling plan under the truncated lifetime test at a pre-determined time for Rama distribution and obtain the smallest sample size to ensure specified mean life for consumer's risk.…”

Section: Introductionmentioning

confidence: 99%

Acceptance sampling plan using new truncated Weibull-X family based on run lengths of conforming items

2020

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In this paper, we develop two acceptance sampling plans where the lifetimes of the products follow Weibull Exponential and Weibull Lomax distributions both belonging to the new truncated Weibull-X family of distributions based on run lengths of the conforming items.The model parameters are estimated by using the maximum likelihood method contrary to the existing plans where authors have been selecting arbitrary values of the parameters. The efficiency of the proposed plan is established by comparing it with the existing plan based on the average number of inspected items. A real example of failure rates of a piece of electronic equipment operating in a specific mode is presented to illustrate the proposed plans for industrial use.

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Acceptance Sampling Plans for Finite and Infinite Lot Size under Power Lindley Distribution

Cited by 10 publications

References 8 publications

Efficient Process Monitoring Under General Weibull Distribution

Efficient Process Monitoring Under General Weibull Distribution

Acceptance sampling plans under two-parameter Quasi Shanker distribution assuring mean life with an application to manufacturing data

Acceptance sampling plan using new truncated Weibull-X family based on run lengths of conforming items

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