Acceptance sampling

2001 ◽  
pp. 1-1
Author(s):  
Saul I. Gass ◽  
Carl M. Harris
Keyword(s):  
Acceptance Sampling

A New Acceptance Sampling Plans Based on Percentiles For Type II Generalized Half-logistic Distribution

2019 ◽  
Vol 10 (6) ◽  
pp. 1354-1363
Author(s):  
G Srinivasa Rao ◽  
Sd. Jilani ◽  
A Vasudeva Rao ◽  
S. Bhanu Prakash
Keyword(s):  
Logistic Distribution ◽  
Acceptance Sampling ◽  
Type Ii ◽  
Sampling Plans ◽  
Acceptance Sampling Plans

Group acceptance sampling plan for resubmitted lots based on life tests for odds exponential log logistic distribution

2017 ◽  
Vol 34 (8) ◽  
pp. 1343-1351 ◽  
Author(s):  
Rosaiah K. ◽  
Srinivasa Rao Gadde ◽  
Kalyani K. ◽  
Sivakumar D.C.U.
Keyword(s):  
Group Size ◽  
Sampling Plan ◽  
Logistic Distribution ◽  
Acceptance Sampling ◽  
Consumer’S Risk ◽  
Content Type ◽  
Acceptance Sampling Plan ◽  
Minimum Group ◽  
Termination Time ◽  
Group Acceptance

Purpose The purpose of this paper is to develop a group acceptance sampling plan (GASP) for a resubmitted lot when the lifetime of a product follows odds exponential log logistic distribution introduced by Rao and Rao (2014). The parameters of the proposed plan such as minimum group size and acceptance number are determined for a pre-specified consumer’s risk, number of testers and the test termination time. The authors compare the proposed plan with the ordinary GASP, and the results are illustrated with live data example. Design/methodology/approach The parameters of the proposed plan such as minimum group size and acceptance number are determined for a pre-specified consumer’s risk, number of testers and the test termination time. Findings The authors determined the group size and acceptance number. Research limitations/implications No specific limitations. Practical implications This methodology can be applicable in industry to study quality control. Social implications This methodology can be applicable in health study. Originality/value The parameters of the proposed plan such as minimum group size and acceptance number are determined for a pre-specified consumer’s risk, number of testers and the test termination time.

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