Construction of multiple dependent state sampling plan for variables based on logistic distribution
Author(s): Dr. S Geetha and S Saranya
Abstract: Acceptance sampling plans are specific rules used in statistical quality control to reach a decision on acceptance or rejection of lots of manufactured products submitted for inspection subject to the quality requirements of the sampled units. In order to reduce the inspection time and cost, the variable sampling plans are used as it needs comparatively small sample size. The multiple dependent state sampling plan is one of the conditional sampling plans which acquires the sample information from present lot as well as the prior lots for disposition of a lot. The MDS plan is applicable in the situations where lots are submitted for inspection in sequence of production from a process having a constant proportion non-conforming. MDS plan under the assumption of normality are found in literature. In this article, a multiple dependent state sampling plan is developed for sentencing lots of products whose quality characteristics follows a Logistic distribution. The proposed plan is designed by considering the two points on the OC curve, by formulating it as a non-linear optimization problem, when standard deviation is known and unknown. The tables are constructed for the selection of the proposed plan parameters. The proposed plan is compared with the single variable sampling plan based on Logistic distribution.
Dr. S Geetha, S Saranya. Construction of multiple dependent state sampling plan for variables based on logistic distribution. Int J Stat Appl Math 2022;7(1):112-117. DOI: 10.22271/maths.2022.v7.i1b.780
