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DOI: 10.14569/IJACSA.2017.080903
PDF

Root-Cause and Defect Analysis based on a Fuzzy Data Mining Algorithm

Author 1: Seyed Ali Asghar Mostafavi Sabet
Author 2: Alireza Moniri
Author 3: Farshad Mohebbi

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 9, 2017.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: Manufacturing organizations have to improve the quality of their products regularly to survive in today’s competitive production environment. This paper presents a method for identification of unknown patterns between the manufacturing process parameters and the defects of the output products and also of the relationships between the defects. Discovery of these patterns helps practitioners to achieve two main goals: first, identification of the process parameters that can be used for controlling and reducing the defects of the output products and second, identification of the defects that very probably have common roots. In this paper, a fuzzy data mining algorithm is used for discovery of the fuzzy association rules for weighted quantitative data. The application of the association rule algorithm developed in this paper is illustrated based on a net making process at a netting plant. After implementation of the proposed method, a significant reduction was observed in the number of defects in the produced nets.

Keywords: Data mining; association rules; defect analysis; fuzzy sets; root cause analysis; quality

Seyed Ali Asghar Mostafavi Sabet, Alireza Moniri and Farshad Mohebbi, “Root-Cause and Defect Analysis based on a Fuzzy Data Mining Algorithm” International Journal of Advanced Computer Science and Applications(IJACSA), 8(9), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080903

@article{Sabet2017,
title = {Root-Cause and Defect Analysis based on a Fuzzy Data Mining Algorithm},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080903},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080903},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {9},
author = {Seyed Ali Asghar Mostafavi Sabet and Alireza Moniri and Farshad Mohebbi}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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