A New Acceptance Sampling Plans Based on Percentiles
For Type II Generalized Half-logistic Distribution

Rao, G. Srinivasa; Jilani, SD; Rao, A. V. Dattatreya; Prakash, S Bhanu

doi:10.29055/jcms/1122

Cited by 3 publications

(3 citation statements)

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“…These results of the sampling plans demonstrate that when the termination ratio (δ ) and consumer's risk (β ) increases the sample size decreases. The designed sampling plan results through EIKD are compared with the results of New Weibull-Pareto Distribution (14) (NWPD), Type-II Generalized Log Logistic Distribution (6) (TGLLD), and New-Weighted Exponential Distribution (8) (NWED). The comparative study is displayed in Table 1.…”

Section: Resultsmentioning

confidence: 99%

“…Yasar Mahmood et al (4) designed the sampling plans with median as standard average using a skewed Topp-Leone Gompertz distribution with one of parameters as scale parameter, Srinivasa Rao et al designed percentile based acceptance plans based on Odd generalized exponential log logistic distribution (5) and Type-II Generalized Log Logistic Distribution (6) having one of the parameters is a scale parameter. Some more analogous approaches of sampling plans with at least one scale parameter are exponentiated inverted weibull distribution (7) ,new-weighted exponential distribution (8) ,Gumbel distribution (9) contemplated by B. Srinivasa Rao et al, Ghadah Alomani, Amer I. and Al-Omari (10) prepared the sampling plans based on two-parameter Xgamma distribution as α as the scale parameter.…”

Section: Introductionmentioning

confidence: 99%

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Acceptance Sampling Plans based on Percentiles of Exponentiated Inverse Kumaraswamy Distribution

Reddy,

Rao,

Rosaiah

2024

IJST

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Objectives: To prepare the percentile-based acceptance sampling plans for the Exponentiated Inverse Kumaraswamy Distribution (EIKD) at a specific truncation time to inspect the defective lots corresponding to the desired acceptance level. Methods: The failure probability value is estimated using the cumulative probability function F(.) at time ‘t’ which is converted in terms of the scale parameter σ as 100th percentile using quantile function. The minimum size of the sample, Operating Characteristic (OC) and the minimum ratios are calculated for a required levels of consumer’s as well as producer’s risk. Findings: The percentile-based sampling plans are obtained through the minimal size of the sample ‘n’ under a truncated life test with a target acceptance number c in a manner that the proportion of accepting a lot which is not good (consumer’s risk) would not be more than . These values are calculated at The function of probability of acceptance for variations in the quality of a lot (OC function) L(p) of the sample plan are evaluated for the acceptance values of c=1 and c=5. The minimum ratio values are calculated for the acceptability of the lot with producers’ risk of using the sampling plan. Novelty: The modernity of this study is the designing of the acceptance sampling plans to a non-normal data using an asymmetrical distribution that has all three shape parameters. Also, the monitor of the implementation and suitability of statistical quality control and process control aspects using Exponentiated Inverse Kumaraswamy Distribution when compared to other asymmetrical distributions which has at least one scale parameter. Keywords: Sampling plans, Consumer's risk, Operating characteristics function, Truncated life tests, Producer's risk

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Acceptance Sampling Plans based on Percentiles of Exponentiated Inverse Kumaraswamy Distribution

Reddy,

Rao,

Rosaiah

2024

IJST

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“…Recently, Momenkhan (2019) studied the GHLD under accelerated life tests and obtained the classical and Bayesian estimates based on Type-I censoring. Rao et al (2019) discussed the acceptance sampling plans for GHLD. Awodutire et al (2022) obtained estimates of multi-components stress-strength reliability from GHLD.…”

Section: Introductionmentioning

confidence: 99%

Estimation and prediction in generalized half logistic lifetime model using hybrid censored data

Soni

Shukla²,

Kumar

2023

IJQRM

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PurposeThis article aims to develop procedures for estimation and prediction in case of Type-I hybrid censored samples drawn from a two-parameter generalized half-logistic distribution (GHLD).Design/methodology/approachThe GHLD is a versatile model which is useful in lifetime modelling. Also, hybrid censoring is a time and cost-effective censoring scheme which is widely used in the literature. The authors derive the maximum likelihood estimates, the maximum product of spacing estimates and Bayes estimates with squared error loss function for the unknown parameters, reliability function and stress-strength reliability. The Bayesian estimation is performed under an informative prior set-up using the “importance sampling technique”. Afterwards, we discuss the Bayesian prediction problem under one and two-sample frameworks and obtain the predictive estimates and intervals with corresponding average interval lengths. Applications of the developed theory are illustrated with the help of two real data sets.FindingsThe performances of these estimates and prediction methods are examined under Type-I hybrid censoring scheme with different combinations of sample sizes and time points using Monte Carlo simulation techniques. The simulation results show that the developed estimates are quite satisfactory. Bayes estimates and predictive intervals estimate the reliability characteristics efficiently.Originality/valueThe proposed methodology may be used to estimate future observations when the available data are Type-I hybrid censored. This study would help in estimating and predicting the mission time as well as stress-strength reliability when the data are censored.

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Acceptance sampling plans based on percentiles for extended generalized exponential distribution with real data application

Al-Omari,

Alomani

2024

Journal of Radiation Research and Applied Sciences

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A New Acceptance Sampling Plans Based on Percentiles For Type II Generalized Half-logistic Distribution

Cited by 3 publications

References 0 publications

Acceptance Sampling Plans based on Percentiles of Exponentiated Inverse Kumaraswamy Distribution

Acceptance Sampling Plans based on Percentiles of Exponentiated Inverse Kumaraswamy Distribution

Estimation and prediction in generalized half logistic lifetime model using hybrid censored data

Acceptance sampling plans based on percentiles for extended generalized exponential distribution with real data application

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