Odd generalized exponential log logistic distribution: A new acceptance sampling plans based on percentiles

Rao, G. Srinivasa; Rosaiah, K.; Sivakumar, D. C. U.; Kalyani, K.

doi:10.11591/ijaas.v8.i3.pp176-183

Cited by 3 publications

(2 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If the data ascertained as non-normal a surpassing approach is essential to draw the sampling plans. 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%

Acceptance Sampling Plans based on Percentiles of Exponentiated Inverse Kumaraswamy Distribution

Reddy,

Rao,

Rosaiah

2024

IJST

View full text Add to dashboard Cite

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

show abstract

Section: Introductionmentioning

confidence: 99%

Acceptance Sampling Plans based on Percentiles of Exponentiated Inverse Kumaraswamy Distribution

Reddy,

Rao,

Rosaiah

2024

IJST

View full text Add to dashboard Cite

show abstract

“…Many authors have created single sampling strategies for a wide range of distributions. Gupta and Gupta [3], Gupta [4], Kantam et al [5], Tsai and Wu [6], Balakrishnan et al [7], and Rao et al [8] have all emerged recently.…”

Section: Introductionmentioning

confidence: 99%

Double Acceptance Sampling Plan for Odd Generalized Exponential Log-logistic Distribution Based on Truncated Life Test

D.C.U.¹,

Rao

Rosaiah

et al. 2023

Digital Manufacturing Technology

View full text Add to dashboard Cite

According to the results of industrial research, product failure time is correlated with fatigue weakness, which is typically produced by repeated stress variations. A double acceptance sampling strategy was presented for shortened life tests where the lifespan of test products follows an odd generalized exponential log-logistic distribution (OGELLD), according to the findings of this study. The minimum sample sizes for the first and second samples are calculated using a producer’s risk of 0.05 to ensure that the actual median life is greater than the specified life at the chosen consumer confidence level. Based on various ratios of genuine median life to stipulated life, we analyzed operational features; we observed that reduced producer risk at the defined level was associated with the lowest median ratios to the specified level. Finally, an illustration is offered to help in the grasp of the suggested framework.

show abstract

Double-Acceptance Sampling Plan for Exponentiated Fréchet Distribution with Known Shape Parameters

Babu

Rao

Rosaiah

2021

Mathematical Problems in Engineering

Self Cite

View full text Add to dashboard Cite

We suppose that a product’s lifetime follow the exponentiated Fréchet distribution of defined shape parameters. Based on this assumption, a double-acceptance sampling plan is constructed. The zero and one failure framework is essentially thought of: if no errors are found from the first sample, then the lot is approved; also, if at least two failures occur, it is rejected. In the first sample, if one failure is observed, then the second sample is taken and decided for the same length as the first one. The cumulative sample sizes of the first and second samples are determined on the basis of the stated confidence level of the consumer to ensure that the actual median is longer than the given life. As indicated by the various ratios of the actual median life to specified median lifetime, the operating characteristics are calculated and placed in presented tables. To decrease the risk of the producer at the predefined level, the minimum ratios of this sort are additionally obtained. Lastly, examples are provided for representation reasons for the proposed model.

show abstract

Odd generalized exponential log logistic distribution: A new acceptance sampling plans based on percentiles

Cited by 3 publications

References 26 publications

Acceptance Sampling Plans based on Percentiles of Exponentiated Inverse Kumaraswamy Distribution

Acceptance Sampling Plans based on Percentiles of Exponentiated Inverse Kumaraswamy Distribution

Double Acceptance Sampling Plan for Odd Generalized Exponential Log-logistic Distribution Based on Truncated Life Test

Double-Acceptance Sampling Plan for Exponentiated Fréchet Distribution with Known Shape Parameters

Contact Info

Product

Resources

About