Optimal designing of variables tightened-normal-tightened sampling scheme by minimising the average sample number

Author(s):  
S. Balamurali ◽  
M. Usha
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.


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.


2010 ◽  
Vol 2010 ◽  
pp. 1-15 ◽  
Author(s):  
Yan Li ◽  
Xiaolong Pu

As a helpful guide for applications, the alternative hypotheses of the three-hypothesis test problems are designed under the required error probabilities and average sample number in this paper. The asymptotic formulas and the proposed numerical quadrature formulas are adopted, respectively, to obtain the hypothesis designs and the corresponding sequential test schemes under the Koopman-Darmois distributions. The example of the normal mean test shows that our methods are quite efficient and satisfactory for practical uses.


2005 ◽  
Vol 34 (3) ◽  
pp. 799-809 ◽  
Author(s):  
S. Balamurali ◽  
Heekon Park ◽  
Chi-Hyuck Jun ◽  
Kwang-Jae Kim ◽  
Jaewook Lee

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Müjgan Zobu ◽  
Vedat Sağlam

The control of traffic intensity is one of the important problems in the study of queueing systems. Rao et al. (1984) developed a method to detect changes in the traffic intensity in queueing systems of the and types based on the Sequential Probability Ratio Test (SPRT). In this paper, SPRT is theoretically investigated for two different phase-type queueing systems which consist of hyperexponential and mixed Erlang. Also, for testing against , Operating Characteristic (OC) and Average Sample Number (ASN) functions are obtained with numerical methods using multipoint derivative equations according to different situations of and type errors. Afterward, numerical illustrations for each model are provided with Matlab programming.


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