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Probability Constrained Optimization as a Tool for Functional Design for Six Sigma

Summary: [This abstract is based on the author’s abstract.]In the overall design of a system, an important factor is the functional design in which the means and tolerances of the design variables are determined with respect to the demands of quality versus those of cost. Probability constrained optimization is investigated as a means of producing a functional design that focuses on the goal of design for Six Sigma. A maximum system probability of nonconformance is obtained from a prescribed defect rate that provides the primary design constraint. The production cost provides the objective function to be minimized in order to determine the design parameters. All three quality metrics and robustness are inherent in the approach. The design of an electro-mechanical servo system illustrates the practicality and potential of the approach.

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  • Topics: Six Sigma, Engineering
  • Keywords: Design for Six Sigma (DFSS), Cost-benefit analysis, Defects, Mean, Tolerance limits, Probability, Case study
  • Author: Savage, Gordon J.
  • Journal: Quality Engineering