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Short-Run Contexts and Imperfect Testing for Continuous Sampling Plans

Department of Statistics, University of California, Riverside, CA 92521, USA
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Algorithms 2018, 11(4), 46; https://doi.org/10.3390/a11040046
Received: 8 February 2018 / Revised: 5 April 2018 / Accepted: 7 April 2018 / Published: 12 April 2018
Continuous sampling plans are used to ensure a high level of quality for items produced in long-run contexts. The basic idea of these plans is to alternate between 100% inspection and a reduced rate of inspection frequency. Any inspected item that is found to be defective is replaced with a non-defective item. Because not all items are inspected, some defective items will escape to the customer. Analytical formulas have been developed that measure both the customer perceived quality and also the level of inspection effort. The analysis of continuous sampling plans does not apply to short-run contexts, where only a finite-size batch of items is to be produced. In this paper, a simulation algorithm is designed and implemented to analyze the customer perceived quality and the level of inspection effort for short-run contexts. A parameter representing the effectiveness of the test used during inspection is introduced to the analysis, and an analytical approximation is discussed. An application of the simulation algorithm that helped answer questions for the U.S. Navy is discussed. View Full-Text
Keywords: CSP-1; sampling plan; harold dodge; simulation algorithm; imperfect testing; short-run contexts CSP-1; sampling plan; harold dodge; simulation algorithm; imperfect testing; short-run contexts
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Rodriguez, M.; Jeske, D.R. Short-Run Contexts and Imperfect Testing for Continuous Sampling Plans. Algorithms 2018, 11, 46.

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