scholarly journals Modified Average Sample Number for Improved Double Sampling Plan Based on Truncated Life Test Using Exponentiated Distributions

2020 ◽  
Vol 8 (5) ◽  
pp. 542-550
Author(s):  
O. S. Deepa
Keyword(s):  
Sampling Plan ◽  
Double Sampling ◽  
Life Test ◽  
Sample Number ◽  
Average Sample Number ◽  
Truncated Life Test ◽  
Average Sample

scholarly journals Design of SkSP-R Plan for Popular Statistical Distributions

2022 ◽  
Vol 19 (1) ◽  
Author(s):  
Jaffer Hussain ◽  
S Balamurali ◽  
Muhammad Aslam
Keyword(s):  
Optimization Problem ◽  
Statistical Distributions ◽  
Life Test ◽  
Lifetime Distributions ◽  
Sample Number ◽  
Average Sample Number ◽  
Sampling Schemes ◽  
Exponentiated Weibull ◽  
Truncated Life Test ◽  
Average Sample

The design of a Skip-lot sampling plan of type SkSP-R is presented for time truncated life test for the Weibull, Exponentiated Weibull, and Birnbaum-Saunders lifetime distributions. The plan parameters of the SkSP-R plan under these three distributions are determined through a nonlinear optimization problem. Tables are also constructed for each distribution. The advantages of the proposed plan over the existing sampling schemes are discussed. Application of the proposed plan is explained with the help of an example. The Birnbaum-Saunders distribution is economically superior to other two distributions in terms of minimum average sample number.

scholarly journals Design of SkSP-R Variables Sampling Plans

2015 ◽  
Vol 38 (2) ◽  
pp. 413-429 ◽  
Author(s):  
Muhammad Aslam ◽  
Saminathan Balamurali ◽  
Chi-Hyuck Jun ◽  
Batool Hussain
Keyword(s):  
Nonlinear Optimization ◽  
Optimization Problem ◽  
Sampling Plan ◽  
Producer’S Risk ◽  
Sample Number ◽  
Sampling Plans ◽  
Average Sample Number ◽  
Nonlinear Optimization Problem ◽  
Better Than ◽  
Average Sample

In this paper, we present the designing of the skip-lot sampling plan including the re-inspection  called SkSP-R. The plan parameters of the proposed plan are determined through a  nonlinear optimization problem by minimizing the average sample number satisfying both the producer's risk and the consumer's risks. The proposed plan is shown to perform better than the existing sampling plans in terms of the average sample number. The application of the proposed plan is explained with the help of illustrative examples.

Designing of Variables Repetitive Group Sampling Plan Involving Minimum Average Sample Number

2005 ◽  
Vol 34 (3) ◽  
pp. 799-809 ◽  
Author(s):  
S. Balamurali ◽  
Heekon Park ◽  
Chi-Hyuck Jun ◽  
Kwang-Jae Kim ◽  
Jaewook Lee
Keyword(s):  
Sampling Plan ◽  
Sample Number ◽  
Average Sample Number ◽  
Repetitive Group Sampling ◽  
Average Sample

scholarly journals On Sequential Probability Sampling Plan for a Truncated Life Tests Using Rayleigh Distribution

2021 ◽  
pp. 1-7
Author(s):  
A. B. Zoramawa ◽  
S. U. Gulumbe
Keyword(s):  
Life Time ◽  
Rayleigh Distribution ◽  
Sampling Plan ◽  
Double Sampling ◽  
Sample Number ◽  
Probability Sampling ◽  
Truncated Life Test ◽  
Life Tests ◽  
Sequential Probability ◽  
Minimum Sample

This paper proposed a sequential probability sampling plan for a truncated life test using a Rayleigh distribution from  a designed double sampling plans where the interest was to obtain the minimum sample size necessary to assure that the average life time of a product is longer than the default life time at the specified consumer’s and producer’s confidence level. Estimations of minimum sample, acceptance and rejection numbers obtained are analyzed and presented to explain the usefulness of sequential plans in relation to single and double sampling plan. Probability of acceptance (Pa), Average sample number (ASN) and Average outgoing quality (AOQ) for the plans are computed. The three regions; acceptance, continue sampling and rejection were determined. The five points necessary to plot ASN curve were also computed and presented.

scholarly journals A Two-stage Group Sampling Plan Based on Truncated Life Tests for an Odd Generalized Exponential Log-logistic Distribution

2019 ◽  
pp. 1-14
Author(s):  
D. C. U. Sivakumar ◽  
G. Srinivasa Rao ◽  
K. Rosaiah ◽  
K. Kalyani
Keyword(s):  
Group Size ◽  
Sampling Plan ◽  
Logistic Distribution ◽  
Acceptance Sampling ◽  
Two Stage ◽  
Sample Number ◽  
Average Sample Number ◽  
Acceptance Sampling Plan ◽  
Group Acceptance ◽  
Average Sample

In this article, a time truncated life test based on two-stage group acceptance sampling plan is proposed for lifetime of an item follows odd generalized exponential log-logistic distribution (OGELLD). The ability about the lot acceptance can be made in the first or second stage according to the number of failures from each group. The optimal parameters for the proposed plan are determined such that both producer’s as well as consumer’s risks are contented simultaneously for the specified unreliability when group size and test duration are specified. The efficiency of the proposed sampling plan is evaluated in terms of average sample number with the existing sampling plan. The results are explained with the help of industrial example.  Using exploratory data analysis and then goodness-of-fit, we show a rough indication of the goodness of fit for our model by plotting the superimposed for the data shows that the OGELLD is a good fit and also it is emphasized with Q-Q plot, displayed in Fig. 1. We observed from the tables / results that the number of groups required decrease as the group size increases from  and also the ASN increases marginally, sample size decreases as the group size increases, which indicates that a larger group size may be more economical and it reduces the experimental time and cost. We proposed two-stage group acceptance sampling plan, since it performs much better in terms of the average sample number (ASN) and the operating characteristics than in single-stage group acceptance sampling plan. The advantage of two stage group sampling plan is that it reduces the average sample number (ASN) as compared to the GASP.

scholarly journals Inspection plan for COVID-19 patients for Weibull distribution using repetitive sampling under indeterminacy

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
G. Srinivasa Rao ◽  
Muhammad Aslam
Keyword(s):  
Weibull Distribution ◽  
Sample Size ◽  
Research Work ◽  
Sampling Plan ◽  
Design Parameters ◽  
Sample Number ◽  
Sampling Plans ◽  
Average Sample Number ◽  
Size Acceptance ◽  
Average Sample

Abstract Background This research work is elaborated investigation of COVID-19 data for Weibull distribution under indeterminacy using time truncated repetitive sampling plan. The proposed design parameters like sample size, acceptance sample number and rejection sample number are obtained for known indeterminacy parameter. Methods The plan parameters and corresponding tables are developed for specified indeterminacy parametric values. The conclusion from the outcome of the proposed design is that when indeterminacy values increase the average sample number (ASN) reduces. Results The proposed repetitive sampling plan methodology application is given using COVID-19 data belong to Italy. The efficiency of the proposed sampling plan is compared with the existing sampling plans. Conclusions Using the tables and COVID-19 data illustration, it is concluded that the proposed plan required a smaller sample size as examined with the available sampling plans in the literature.

scholarly journals Mixed Variables-Attributes Test Plans for Single and Double Acceptance Sampling under Exponential Distribution

2011 ◽  
Vol 2011 ◽  
pp. 1-15 ◽  
Author(s):  
Yan Li ◽  
Xiaolong Pu ◽  
Dongdong Xiang
Keyword(s):  
Exponential Distribution ◽  
Operating Characteristic ◽  
Acceptance Sampling ◽  
Sample Sizes ◽  
Sample Number ◽  
Sampling Plans ◽  
Average Sample Number ◽  
Mixed Variables ◽  
Average Sample

The mixed variables-attributes test plans for single acceptance sampling are proposed to protect “good lots” from attributes aspect and to optimize sample sizes from variables aspect. For the single and double mixed plans, exact formulas of the operating characteristic and average sample number are developed for the exponential distribution. Numerical illustrations show that the mixed sampling plans have some advantages over the variables plans or attributes plans alone.

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