An alternative evaluation of FMEA: Fuzzy ART algorithm

Quality and Reliability Engineering International

Volumn 25, Issue 6, 2009, Pages 647-661

  Keskin, Gülşen Aydin ^a   Özkan, Coşkun ^a  

^a KOCAELI UNIVERSITY   (Turkey)

Author keywords

Clustering analysis; Failure modes and effect analysis (FMEA); Fuzzy adaptive resonance theory (fuzzy ART)

Indexed keywords

ADAPTIVE RESONANCE THEORY; ART NETWORKS; ARTIFICIAL NEURAL NETWORK; CLUSTERING ANALYSIS; CLUSTERING PROBLEMS; FAILURE MODE AND EFFECTS ANALYSIS; FUZZY ADAPTIVE RESONANCE THEORIES; FUZZY ADAPTIVE RESONANCE THEORY (FUZZY ART); FUZZY ART; MANUFACTURING INDUSTRIES; PRODUCTION QUALITY; RISK PRIORITY NUMBER;

FAILURE MODES; LEARNING ALGORITHMS; NEURAL NETWORKS; RELIABILITY ANALYSIS; RESONANCE; SAFETY FACTOR;

QUALITY ASSURANCE;

EID: 70349554431     PISSN: 07488017     EISSN: 10991638     Source Type: Journal    
DOI: 10.1002/qre.984     Document Type: Article

References (31)

1. Price CJ, Snooke NA, Lewis SD. A layered approach to automated electrical safety analysis in automotive environments. Computers in Industry 2006; 57:451-461.
2. Franceschini F, Galetto M. A new approach for evaluation of risk priorities of failure modes in FMEA. International Journal of Production Research 2001; 39(13):2991-3002.
3. Kara-Zaitri C, Keller AZ, Fleming PV. A smart failure mode and effect analysis package. Proceedings of the Annual Reliability and Maintainability Symposium. IEEE: Silver Spring, MD, 1992. 0149-144X/92/0000-0414.
4. Nepal BP, Yadav OP, Monplaisir L, Murat A. A framework for capturing and analyzing the failures due to system/component interactions. Quality and Reliability Engineering International 2008; 24:265-289.
5. Sankar NR, Prabhu BS. Application of fuzzy logic to matrix FMECA. Review of Progress in Quantitative Nondestructive Evaluation, vol.20. American Institute of Physics, 2001; 1-56396-988-2/01.
6. Sharma RK, Kumar D, Kumar P. Modeling system behavior for risk and reliability analysis using KBARM. Quality and Reliability Engineering International 2007; 23:973-998.
7. Garcia PAA, Schirru R, Melo PFFE. A fuzzy data envelopment analysis approach for FMEA. Progress in Nuclear Energy 2005; 46(3-4):359-373.
8. Burwick T, Joublin F. Optimal algorithmic complexity of Fuzzy ART. Neural Processing Letters 1998; 7:37-41.
9. Carpenter GA, Milenova BL. ART neural networks for medical data analysis and fast distributed learning. Artificial Neural Networks in Medicine and Biology. Göteborg University: Sweden, 2000.
10. Dagher I. ART networks with geometrical distances. Journal of Discrete Algorithms 2006; 4(4):538-553.
11. Kondadadi R, Kozma R. A Modified Fuzzy ART for Soft Document Clustering. IEEE: Silver Spring, MD, 2002. 0-7803-7278-6/02.
12. Pacella M, Semeraro Q, Anglani A. Manufacturing quality control by means of a Fuzzy ART network trained on natural process data. Artificial Intelligence 2004; 17:83-96.
13. Suresh NC, Kaparthi S. Performance of Fuzzy ART neural network for group technology cell-formation. International Journal of Production Research 1994; 32:1693-1713.
14. Carpenter GA, Grossberg S, Rosen DB. Fuzzy ART: Fast sTable learning and categorization of analog patterns by an adaptive resonance system. Neural Networks 1991; 4:759-771.
15. Huang J, Georgiopoulos M, Heileman GL. Properties of Learning in Fuzzy ART. IEEE: Silver Spring, MD, 1994. 0-7803-1901-X/94.
16. Munoz A. Compound key word generation from document databases using a hierarchical clustering ART model. Intelligent Data Analysis 1997; 1:24-48.
17. Blume M, Esener SC. An efficient mapping of Fuzzy ART onto a neural architecture. Neural Networks Letter 1997; 10(3):409-411.
18. Georgiopoulos M, Dagher I, Heileman GL, Bebis G. Properties of learning of a Fuzzy ART variant. Neural Networks 1999; 12:837-850.
19. Chung I, Lin C-J, Lin C-T. A GA-based fuzzy adaptive learning control network. Fuzzy Sets and Systems 2000; 112:65-84.
20. Tomida S, Hanai T, Honda H, Kobayashi T. Gene expression analysis using Fuzzy ART. Genome Informatics 2001; 12:245-246.
21. Kim M-H, Jang D-S, Yang Y-K. A robust-invariant pattern recognition model using Fuzzy ART. Pattern Recognition 2001; 34:1685-1696.
22. Tomida S, Hanai T, Honda H, Kobayashi T. Analysis of expression profile using Fuzzy ART. Bioinformatics 2002; 18(8):1073-1083.
23. Anagnostopoulos GC, Georgiopoulos M. Category regions as new geometrical concepts in Fuzzy ART and Fuzzy ARTMAP. Neural Networks 2002; 15:1205-1221.
24. Kato N, Kobayashi T, Honda H. Gene expression analysis of heat shock response using Fuzzy ART. Genome Informatics 2002; 13:272-273.
25. Lubkin J, Cauwenberghs G. VLSI implementation of fuzzy adaptive resonance and LVQ. Analog Integrated Circuits and Signal Processing 2002; 30:149-157.
26. Park S, Suresh NC. Performance of Fuzzy ART neural network and hierarchical clustering for part-machine grouping based on operation sequences. International Journal of Production Research 2003; 41(14):3185-3216.
27. Gomez SA, Chesnevar CI. Integrating defeasible argumentation with Fuzzy ART neural networks for pattern classification. Journal of Computer Science and Technology 2004; 4(1):45-51.
28. Peker A, Kara Y. Parameter setting of the Fuzzy ART neural network to part-machine cell formation problem. International Journal of Production Research 2004; 42(6):1257-1278.
29. Cinque L, Foresti G, Lombardi L. A clustering fuzzy approach for image segmentation. Pattern Recognition 2004; 37:1797-1807.
30. Lopes MLM, Minussi CR, Lotufo ADP. Electric load forecasting using a Fuzzy ART&ARTMAP neural network. Applied Soft Computing 2005; 5:235-244.
31. Lee SY, Fischer GW. Grouping parts based on geometrical shapes and manufacturing attributes using a neural network. Journal of Intelligent Manufacturing 1999; 10:199-209.