In this manuscript, a group acceptance sampling plan (GASP) is developed when the lifetime of the items follows odd generalized exponential log-logistic distribution (OGELLD), the multiple number of items as a group can be tested simultaneously in a tester. The design parameters such as the minimum group size and the acceptance number are derived when the consumer's risk and the test termination time are specified. The operating characteristic (OC) function values are calculated (intended) according to various quality levels and the minimum ratios of the true average life to the specified average life at the specified producer's risk are derived. The methodology is illustrated through real data.
Abstract:In this paper, acceptance sampling plans are developed for the odds exponential log logistic distribution (OELLD) introduced by Rosaiah et al.[1] based on lifetime percentiles when the life test is truncated at a predetermined time. The minimum sample size necessary to ensure the specified lifetime percentile is obtained under a given customer's risk. The operating characteristic values of the sampling plans as well as the producer's risk are presented. One example with real data set is also given as an illustration.
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.
Abstract:We propose a distribution called Odds Exponential Log Logistic Distribution (OELLD), which is an odds family of distribution. Its hazard rate is an increasing and decreasing function based on the value of the parameter. Explicit expressions for the ordinary moments, L-moments, quantile, generating functions, Bonferroni Curve, Lorenz Curve, Gini's index and order statistics are derived. The parameters of the proposed distribution are estimated by using maximum likelihood method and also illustrated by a lifetime data set.
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