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
2015 ◽  
Vol 38 (2) ◽  
pp. 413-429 ◽  
Author(s):  
Muhammad Aslam ◽  
Saminathan Balamurali ◽  
Chi-Hyuck Jun ◽  
Batool Hussain

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.


Author(s):  
D. C. U. Sivakumar ◽  
G. Srinivasa Rao ◽  
K. Rosaiah ◽  
K. Kalyani

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.


2016 ◽  
Vol 13 (10) ◽  
pp. 6568-6575
Author(s):  
Muhammad Aslam ◽  
Ali Hamed S Algarni ◽  
Ramsha Saeed

In this paper, sampling plan using exact and approximated approaches is presented when the quality of interest follows the exponential distribution. The designing both presented using the repetitive group sampling plan. The design parameters of the proposed sampling plans are determined through non-linear optimization. The efficiency of proposed sampling plans is compared with the existing sampling plans in terms of average sample number. The application of the proposed plans is discussed by industrial data.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
G. Srinivasa Rao ◽  
Muhammad Aslam

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.


2011 ◽  
Vol 2011 ◽  
pp. 1-15 ◽  
Author(s):  
Yan Li ◽  
Xiaolong Pu ◽  
Dongdong Xiang

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.


2017 ◽  
Vol 40 (7) ◽  
pp. 2240-2248 ◽  
Author(s):  
Saminathan Balamurali ◽  
Jambulingam Subramani

Skip-lot sampling plans have been widely used in industries to reduce the inspection efforts on products that have an excellent quality history. These skip-lot sampling schemes are economically advantageous and useful to minimize the cost of the inspection of the final lots. Also, the skip-lot concept is sound and useful in the design of sampling plans. In this paper, we propose a designing methodology to determine the optimal parameters of a skip-lot sampling plan of type SkSP-2 when the quality characteristic under study follows a normal distribution. The optimal plan parameters are determined to minimize the average sample number subject to satisfying the producer’s and consumer’s risks simultaneously at the acceptable and limiting quality levels, respectively. An optimization problem is formulated in order to construct tables for determining the optimal parameters of the proposed sampling plan for both known and unknown standard deviation cases and the results are compared with the variables single sampling plans.


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