A New Fuzzy Method for Assessing Six Sigma Measures

Authors

  • Abolfazl Kazemi Assistant Professor, Faculty of Industrial and Mechanical Engineering, Qazvin branch, Islamic Azad University, Qazvin, Iran
  • Alireza Alinezhad Faculty of industrial and mechanical engineering, Qazvin branch, Islamic Azad Univeristy, Qazvin, Iran
  • Mohammad Saidi Mehrabad Professor, Department of Industrial Engineering, Iran University of Science and Technology, Tehran, , Iran
  • Seyed Habib A Rahmati Instructor, Faculty of Industrial and Mechanical Engineering, Qazvin branch, Islamic Azad University, Qazvin, Iran
Abstract:

Six-Sigma has some measures which measure performance characteristics related to a process. In most of the traditional methods, exact estimation is used to assess these measures and to utilize them in practice. In this paper, to estimate some of these measures, including Defects per Million Opportunities (DPMO), Defects per Opportunity (DPO), Defects per unit (DPU) and Yield, a new algorithm based on Buckley's estimation approach is introduced. The algorithm uses a family of confidence intervals to estimate the mentioned measures. The final results of introduced algorithm for different measures are triangular shaped fuzzy numbers. Finally, since DPMO, as one of the most useful measures in Six-Sigma, should be consistent with costumer need, this paper introduces a new fuzzy method to check this consistency. The method compares estimated DPMO with fuzzy customer need. Numerical examples are given to show the performance of the method. All rights reserved

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Journal title

volume 6  issue 13

pages  39- 47

publication date 2013-09-01

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