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A unified approach for modeling and designing attribute sampling plans for monitoring dependent production processes

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Title A unified approach for modeling and designing attribute sampling plans for monitoring dependent production processes
 
Creator VELLAISAMY, P
SANKAR, S
 
Subject successes
trials
number
production process
process monitoring
probabilistic models
designing sampling plans
average sample number
recurrence relations
acceptance probabilities
algorithms
 
Description In this paper, we consider a probabilistic model to represent some general dependent production processes and present a unified approach for designing attribute sampling plans for monitoring the ongoing production process. This model includes the classical iid model, independent model, Markov-dependent model and previous-sum dependent model, to mention a few. Some important properties of this model are established. We derive the recurrence relations for the probability distribution of the sum of n consecutive characteristics observed from the process. Using these recurrence relations, we present efficient algorithms for designing optimal single and double sampling plans for attributes, for monitoring the ongoing production process. Our algorithmic approach, which uses effectively the recurrence relations, yields a direct and an exact method, unlike many approximate methods adopted in the literature. Several interesting examples concerning specific models are discussed and a few tables for some special cases are also presented. It is demonstrated that the optimal double sampling plans lead to about 42% reduction in average sample number over the single sampling plans for process monitoring.
 
Publisher SPRINGER
 
Date 2011-08-29T09:04:07Z
2011-12-26T12:58:31Z
2011-12-27T05:48:36Z
2011-08-29T09:04:07Z
2011-12-26T12:58:31Z
2011-12-27T05:48:36Z
2005
 
Type Article
 
Identifier METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY, 7(3), 307-323
1387-5841
http://dx.doi.org/10.1007/s11009-005-4519-7
http://dspace.library.iitb.ac.in/xmlui/handle/10054/12035
http://hdl.handle.net/10054/12035
 
Language en