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Attribute Acceptance Sampling as a Tool for Verifying Requirements Using Monte Carlo Simulation

Summary: [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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  • Topics: Statistical Process Control (SPC), Sampling
  • Keywords: Acceptance sampling, Discrete data, Monte Carlo methods, Statistical quality control (SQC), Verification, Simulations
  • Author: White Jr., K. Preston; Johnson, Kenneth L.; Creasey Jr., Roy R.
  • Journal: Quality Engineering