Progressively Censored Reliability Sampling Plans for the Weibull Distribution

Balasooriya, Uditha; Saw, Sutaip L. C.; Gadag, Veeresh

doi:10.1080/00401706.2000.10485995

Cited by 77 publications

(21 citation statements)

References 18 publications

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“…The design of life test sampling plans involving single sampling plans by variables when items are run at normal stress condition has been studied by many authors, for example Epstein andSobel (1953, 1955) , Epstein (1954), Aroian (1964), Bulgren and Hewette (1973), Kockerlakota and Balakrishnan (1986), Fairbanks (1988), Balasooriya (1995), Balasooriya and Saw (1998) for exponential distribution, Hatter and Moore (1980), Fertig and Mann (1980) and Schneider (1989) for Weibull distribution, Balasooriya et al (2000) have presented progressively failure-censored sampling plans and Balasooriya and Low (2004)) have extended their results to the case with competing causes of failure.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimum time-censored simple ramp-stress accelerated life test sampling plan for the log-logistic distribution

Srivastava

Sharma

2015

Journal of Quality in Maintenance Engineering

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Purpose -Acceptance sampling plans are designed to decide about acceptance or rejection of a lot of products on the basis of sample drawn from it. Accelerating the life test helps in obtaining information about the lifetimes of high reliability products quickly. The purpose of this paper is to formulate an optimum time censored acceptance sampling plan based on ramp-stress accelerated life test (ALT) for items having log-logistic life distribution. The log-logistic life distribution has been found appropriate for highly reliable components such as power system components and insulating materials. Design/methodology/approach -The inverse power relationship has been used to model stress-life relationship. It is meant for analyzing data for which the accelerated stress is nonthermal in nature, and frequently used as an accelerating stress for products such as capacitors, transformers, and insulators. The method of maximum likelihood is used for estimating design parameters. The optimal test plan is obtained by minimizing variance of test-statistic that decides on acceptability or rejectibility of lot. The optimal test plan finds optimal sample size, stress rates, sample proportion allocated to each stress and lot acceptability constant such that producer's risk and consumer's risk is satisfied. Findings -Asymptotic variance plays a pivotal role in determining the sample size required for a sampling plan for deciding the acceptance/rejection of a lot. The sample size is minimized by optimally designing a ramp-stress ALT so that the asymptotic variance is minimized. Originality/value -The model suggested is of use to quality control and reliability engineers dealing with highly reliable items.

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Section: Literature Reviewmentioning

confidence: 99%

Optimum time-censored simple ramp-stress accelerated life test sampling plan for the log-logistic distribution

Srivastava

Sharma

2015

Journal of Quality in Maintenance Engineering

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“…There are three different methods of accelerating a life test: (1) Increase the use-rate of the product. (2) Increase the aging-rate of the product. (3) Increase the level of stress under which test units operate.…”

Section: Introductionmentioning

confidence: 99%

Bayesian Sampling Plans With Progressive Censoring and Warranty Policy

Tsai

2008

Int. J. Rel. Qual. Saf. Eng.

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The paper investigates the design of Bayesian sampling plan for the exponential lifetime model under progressive type-II censoring, in which items are manufactured in batches and sold to consumers with a general rebate warranty policy. Assume that the mean lifetime of items is random and varies from lot to lot. A cost model consists of the cost per item on test, the cost per item of test time and the costs of rejecting and accepting an item is established, and an algorithm is provided to determine the optimal Bayesian sampling plan which minimizes the expected average cost per lot. The use of the proposed method is illustrated by numerical results and an example. A sensitivity study is conducted to evaluate the influences of the removal scheme and using incorrect estimates for the hyper-parameters on the proposed sampling plans. The proposed method can be extended to the Weibull lifetime model as its shape parameter is known.

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“…Inference, sampling design and generalization based on progressively censored samples were studied by many authors, see among others, Balasooriya et al [3], Ng et al [4], Balakrishnan et al [5], Fernandez [6], Soliman [7], Asgharzadeh [8], Ku and Kaya [9], Wu et al [10], Banerjee and Kundu [11] and Raqab et al [12]. However, a little work is introduced in the Bayesian context.…”

Section: Introductionmentioning

confidence: 99%

Inferences using type-II progressively censored data with binomial removals

et al. 2015

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This paper considers the estimation problem for Burr type-X model, when the lifetimes are collected under type-II progressive censoring with random removals, where the number of units removed at each failure time follows a binomial distribution. The methods of maximum likelihood as well as the Bayes procedure to derive both point and interval estimates of the parameters are used. The expected test time to complete the censoring test is computed and analyzed for different censoring schemes. The effect of the binomial distribution parameter p on the expected test time under progressive censoring and the relative expected test time over the complete sample are investigated. Monte Carlo simulations are performed to compare and evaluate the performance of different methods. Furthermore, an example with a real data set is presented for illustrative purposes.

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Progressively Censored Reliability Sampling Plans for the Weibull Distribution

Cited by 77 publications

References 18 publications

Optimum time-censored simple ramp-stress accelerated life test sampling plan for the log-logistic distribution

Optimum time-censored simple ramp-stress accelerated life test sampling plan for the log-logistic distribution

Bayesian Sampling Plans With Progressive Censoring and Warranty Policy

Inferences using type-II progressively censored data with binomial removals

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