Some Group Acceptance Sampling Based on Life Tests from Some Specific Distributions

2019 ◽  
pp. 91-171
Author(s):  
Muhammad Aslam ◽  
Mir Masoom Ali
Keyword(s):  
Acceptance Sampling ◽  
Life Tests ◽  
Group Acceptance

scholarly journals Economic Reliability Group Acceptance Sampling Based on Truncated Life Tests Using Pareto Distribution of the Second Kind

2010 ◽  
Vol 17 (5) ◽  
pp. 725-731 ◽  
Author(s):  
Muhammad Aslam ◽  
Abdur Razzaque Mughal ◽  
Muhammad Hanif ◽  
Munir Ahmad
Keyword(s):  
Pareto Distribution ◽  
Acceptance Sampling ◽  
Life Tests ◽  
Group Acceptance

Group acceptance sampling plans based on time truncated life tests for compound Weibull-exponential distribution

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ayten Yiğiter ◽  
Canan Hamurkaroğlu ◽  
Nazan Danacıoğlu
Keyword(s):  
Acceptance Sampling ◽  
Type I ◽  
Consumer’S Risk ◽  
Producer’S Risk ◽  
Data Set ◽  
Sampling Plans ◽  
Content Type ◽  
Acceptance Sampling Plans ◽  
Life Tests ◽  
Group Acceptance

PurposeAcceptance sampling plans are a decision-making process on the basis of a randomly selected sampling from a party, where it is not possible to completely scan the products for reasons such as time and cost being limited or the formation of damaged products during the inspection. For some products, the life span (time from beginning to failure) may be an important quality characteristic. In this case, the quality control adequacy of the products can be checked with an acceptance sampling plan based on the truncated life test with a censored scheme for the lifetime of the products. In this study, group acceptance sampling plans (GASPs) based on life tests are studied under the Type-I censored scheme for the compound Weibull-exponential (CWE) distribution.Design/methodology/approachGASPs based on life tests under the Type-I censored scheme for the CWE distribution are developed by using both the producer's risk and the consumer's risk.FindingsIn this study, optimum sample size, optimum number of groups and acceptance number are obtained under the Type-I censored scheme for the CWE distribution. Real data set illustration is given to show GASPs how to be used for the industry applications.Originality/valueDifferent from acceptance sampling plans with just considering the producer's risk, GASPs are constructed by using two-point approach included both the producer's risk and the consumer's risk for CWE distribution.

Group acceptance sampling plan for resubmitted lots based on life tests for odds exponential log logistic distribution

2017 ◽  
Vol 34 (8) ◽  
pp. 1343-1351 ◽  
Author(s):  
Rosaiah K. ◽  
Srinivasa Rao Gadde ◽  
Kalyani K. ◽  
Sivakumar D.C.U.
Keyword(s):  
Group Size ◽  
Sampling Plan ◽  
Logistic Distribution ◽  
Acceptance Sampling ◽  
Consumer’S Risk ◽  
Content Type ◽  
Acceptance Sampling Plan ◽  
Minimum Group ◽  
Termination Time ◽  
Group Acceptance

Purpose The purpose of this paper is to develop a group acceptance sampling plan (GASP) for a resubmitted lot when the lifetime of a product follows odds exponential log logistic distribution introduced by Rao and Rao (2014). The parameters of the proposed plan such as minimum group size and acceptance number are determined for a pre-specified consumer’s risk, number of testers and the test termination time. The authors compare the proposed plan with the ordinary GASP, and the results are illustrated with live data example. Design/methodology/approach The parameters of the proposed plan such as minimum group size and acceptance number are determined for a pre-specified consumer’s risk, number of testers and the test termination time. Findings The authors determined the group size and acceptance number. Research limitations/implications No specific limitations. Practical implications This methodology can be applicable in industry to study quality control. Social implications This methodology can be applicable in health study. Originality/value The parameters of the proposed plan such as minimum group size and acceptance number are determined for a pre-specified consumer’s risk, number of testers and the test termination time.

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