Designing of Chain Sampling Plan under Gamma-Poisson Distribution
P. Jeyadurga1, S. Balamurali2
1P. Jeyadurga, Department of Mathematicss, Kalasalingam Academy of Research and Education College, Krishnankoil (Tamil Nadu), India.
2S. Balamurali, Department of Computer Applications, Kalasalingam Academy of Research and Education College, Krishnankoil (Tamil Nadu), India.
Manuscript received on 24 November 2019 | Revised Manuscript received on 18 December 2019 | Manuscript Published on 30 December 2019 | PP: 711-714 | Volume-9 Issue-1S4 December 2019 | Retrieval Number: A11961291S419/19©BEIESP | DOI: 10.35940/ijeat.A1196.1291S419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: Chain Sampling Plan, Consumer’s Risk, Discriminating Power, Gamma-Poisson Distribution, Producer’s Risk.
Scope of the Article: Block Chain-Enabled IoT Device and Data Security and Privacy