Open AccessSelection of Tightened-Normal-Tightened sampling scheme under the implications of intervened Poisson distribution
Author(s) -
Azarudheen Shahabudheen,
Pradeepa Veerakumari
Publication year - 2019
Publication title -
pakistan journal of statistics and operation research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.354
H-Index - 15
eISSN - 2220-5810
pISSN - 1816-2711
DOI - 10.18187/pjsor.v15i1.2351
Subject(s) - sampling scheme , poisson distribution , sampling (signal processing) , scheme (mathematics) , mathematics , distribution (mathematics) , selection (genetic algorithm) , table (database) , normal distribution , process (computing) , statistics , mathematical optimization , computer science , data mining , artificial intelligence , mathematical analysis , filter (signal processing) , estimator , computer vision , operating system
Tightened-normal-tightened (TNT) sampling scheme is one of the most frequently used sampling schemes for making decisions about the finished product lots by examining certain samples from the lots. TNT sampling scheme includes two attribute sampling plans, one for tightened inspection and other for normal inspection along with switching rules. This paper introduces a procedure for TNT by incorporating two single sampling plans (SSP) under the conditions of intervened Poisson distribution (IPD) for the lots which may have a possibility of some intervention during the production process. The paper also assesses the performance of the proposed scheme procedure through its operating characteristic curves. Also, the unity value table is provided for certain parameters of specified producer’s risk and consumer’s risk for shop floor conditions. Further, the efficiency of proposed TNT scheme over the individual SSP under the conditions of IPD is demonstrated with illustrations.