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QICID: 30053
Title: Attribute Acceptance Sampling as a Tool for Verifying Requirements Using Monte Carlo Simulation
Copyright: ASQ; Taylor & Francis
Author: White Jr., K. Preston; Johnson, Kenneth L.; Creasey Jr., Roy R.
Organization: Department of Systems & Information Engineering, University of Virginia; Statistics & Trending, NASA/
NESC Systems Engineering Office, NASA Marshall Space Flight Center; College of Business & Economics, Longwood
University
Subject: Acceptance sampling; Discrete data; Monte Carlo methods; Statistical quality control (SQC); Verification; Simulations;
Series: Quality Engineering, Vol. 21, No. 2, April 2009, pp. 203 – 214
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Abstract: [This abstract is based on the authors' abstract.]
Acceptance sampling is a statistical approach that can be adapted to verification problems that rely on the outcomes of stochastic experiments. It is shown here how the technique is used to verify a problem of probabilistic design requirements using Monte Carlo simulation. An attribute sampling plan determines the number of simulation replications that must be run and the number of nonconforming replication that can’t be exceeded. An example from NASA’s Constellation Program illustrates the technique. Alternatives to attribute acceptance sampling are suggested to control costs.
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