Optimal designing of SkSP-2 skip-lot sampling plan for normally distributed quality characteristics

2017 ◽  
Vol 40 (7) ◽  
pp. 2240-2248 ◽  
Author(s):  
Saminathan Balamurali ◽  
Jambulingam Subramani
Keyword(s):  
Sampling Plan ◽  
Quality Characteristic ◽  
Optimal Parameters ◽  
Optimal Plan ◽  
Sample Number ◽  
Sampling Plans ◽  
Sampling Schemes ◽  
The Cost ◽  
Optimal Designing ◽  
Average Sample

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.

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.

scholarly journals Optimal Designing of Variables Chain Sampling Plan by Minimizing the Average Sample Number

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
S. Balamurali ◽  
M. Usha
Keyword(s):  
Operating Characteristic ◽  
Characteristic Curve ◽  
Sampling Plan ◽  
Quality Level ◽  
Sample Number ◽  
Acceptable Quality ◽  
Acceptable Quality Level ◽  
Limiting Quality Level ◽  
Optimal Designing ◽  
Average Sample

We investigate the optimal designing of chain sampling plan for the application of normally distributed quality characteristics. The chain sampling plan is one of the conditional sampling procedures and this plan under variables inspection will be useful when testing is costly and destructive. The advantages of this proposed variables plan over variables single sampling plan and variables double sampling plan are discussed. Tables are also constructed for the selection of optimal parameters of known and unknown standard deviation variables chain sampling plan for specified two points on the operating characteristic curve, namely, the acceptable quality level and the limiting quality level, along with the producer’s and consumer’s risks. The optimization problem is formulated as a nonlinear programming where the objective function to be minimized is the average sample number and the constraints are related to lot acceptance probabilities at acceptable quality level and limiting quality level under the operating characteristic curve.

Design and Construction of Plan for Exponential Distribution Using Repetitive Sampling

2016 ◽  
Vol 13 (10) ◽  
pp. 6568-6575
Author(s):  
Muhammad Aslam ◽  
Ali Hamed S Algarni ◽  
Ramsha Saeed
Keyword(s):  
Exponential Distribution ◽  
Linear Optimization ◽  
Sampling Plan ◽  
Design Parameters ◽  
Sample Number ◽  
Sampling Plans ◽  
Industrial Data ◽  
Repetitive Group Sampling ◽  
Average Sample

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.

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.

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

Design of single and double acceptance sampling plans based on neutrosophic sets

2021 ◽  
pp. 1-18
Author(s):  
Gürkan Işik ◽  
İhsan Kaya
Keyword(s):  
Fuzzy Set ◽  
Acceptance Sampling ◽  
Good Representation ◽  
Neutrosophic Sets ◽  
Defective Items ◽  
Sample Number ◽  
Sampling Plans ◽  
Acceptance Sampling Plans ◽  
Different Sources ◽  
Average Sample

Although traditional acceptance sampling plans (ASPs) need certain mass quality characteristics, it is not easy to define them as crisp value in some real case problems. The fuzzy set theory (FST) is one of the popular techniques to model uncertainties of the process and therefore fuzzy ASPs have been offered in the literature. Fuzzy set extensions have been proposed recently for better modeling of the uncertainties having different sources and characteristics. One of these extensions named neutrosophic sets (NSs) can be used to increase the sensitiveness and flexibility of ASPs. The ASPs based on NSs can give ability to classify the items as defective, non-defective and indeterminate. Since the operator can become indecisive for slightly defective items, these plans can provide a good representation of human evaluations under uncertainty. In this study, single and double ASPs are designed based on NSs by using binomial and poisson distributions that are also re-analyzed based on NSs. For this aim, some characteristics functions of ASPs such as probability of accepting a lot (Pa), average outgoing quality (AOQ), average total inspection (ATI) and average sample number (ASN) have also been analyzed based on NSs. Numerical examples are presented to analyze the proposed plans.

The impact of misspecification of the negative binomial shape parameter in sequential sampling plans

1986 ◽  
Vol 16 (3) ◽  
pp. 608-611 ◽  
Author(s):  
W. G. Warren ◽  
Pin Whei Chen
Keyword(s):  
Operating Characteristic ◽  
Shape Parameter ◽  
Negative Binomial ◽  
Sequential Sampling ◽  
Forest Pests ◽  
Sample Number ◽  
Sampling Plans ◽  
Average Sample Number ◽  
The Impact ◽  
Average Sample

Standard sequential sampling plans for determining whether infestations of forest pests have attained critical levels are commonly based on the assumption that the counts follow a negative binomial distribution for which the shape parameter, k, which must be specified, may be difficult to estimate and may well be unstable. This paper studies the effect of misspecification of this parameter on the operating characteristic and average sample number functions of a sequential sampling plan. It appears that slight underestimation of the shape parameter can improve the operating characteristic at little cost, i.e., with only small increase in the average sample number.

scholarly journals Designing of Chain Sampling Plan under Gamma-Poisson Distribution

2019 ◽  
Vol 9 (1S4) ◽  
pp. 711-714
Keyword(s):  
Poisson Distribution ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Sampling Plan ◽  
Conditional Sampling ◽  
Optimal Parameters ◽  
Sampling Plans ◽  
Operating Characteristic Curve

In this manuscript, we discuss the designing procedure of chain sampling plan which is known as one of the conditional sampling plans under gamma-Poisson distribution. We determine the optimal parameters namely, number of items to be chosen for inspection from the lot and number of preceding lots to be considered in order to dispose the current lot by specifying two points on the operating characteristic curve, which is the usual designing approach of sampling plan. The procedure which is used to execute the proposed plan is provided and comparison is made among the proposed plan and existing sampling plans performance.

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