A single input rule modules connected fuzzy FMEA methodology for edible bird nest processing

Advances in Intelligent Systems and Computing

Volumn 223, Issue , 2014, Pages 165-176

  Jong, Chian Haur ^a   Tay, Kai Meng ^a   Lim, Chee Peng ^b  

^a UNIVERSITI MALAYSIA SARAWAK   (Malaysia)

^b DEAKIN UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

BIRDS; COMPUTATION THEORY; FUZZY RULES; RISK ASSESSMENT; SOCIAL NETWORKING (ONLINE); SOFT COMPUTING; WORLD WIDE WEB;

EDIBLE BIRD NESTS; FAILURE MODE AND EFFECTS ANALYSIS; FUZZY INFERENCE SYSTEMS; FUZZY RULE BASE; GOVERNING EQUATIONS; MODELING PROCESS; MONOTONICITY PROPERTY; RISK PRIORITY NUMBER;

FUZZY INFERENCE;

EID: 84912551234     PISSN: 21945357     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-319-00930-8_15     Document Type: Conference Paper

References (18)

1. Xu, K., Tang, L.C., Xie, M., Ho, S.L., Zhu, M.L.: Fuzzy assessment of FMEA for engine systems. Reliab. Eng. Systety Safe. 75, 17-29 (2002)
2. Wang, Y.M., Chin, K.S., Poon, G.K.K., Yang, J.B.: Risk evaluation in failure mode and effects analysis using fuzzy weighted geometric mean. Expert Syst. Appl. 36, 1195-1207 (2009)
3. Liu, J., Martínez, L., Wang, H., Rodríguez, R.M., Novozhilov, V.: Computing with words in risk assessment. Int. J. Comput. Int. Syst. 3, 396-419 (2010)
4. Tay, K.M., Lim, C.P.: Fuzzy FMEA with a guided rules reduction system for prioritization of failures. Int. J. Qual. Reliab. Manag. 23, 1047-1066 (2006)
5. Bowles, J.B., Pelaez, C.E.: Fuzzy logic prioritization of failures in a system failure mode, effect and criticality analysis. Reliab. Eng. Syst. Safety 50, 203-213 (1995)
6. Guimarães, A.C.F., Lapa, C.M.F.: Fuzzy FMEA applied to PWR chemical and volume control system. Progr. Nucl. Energy 44, 191-213 (2004)
7. Pillay, A., Wang, J.: Modified failure mode and effects analysis using approximate reasoning. Reliab. Eng. Syst. Safe. 79, 69-85 (2003)
8. Yang, Z., Bonsall, S., Wang, J.: Fuzzy rule-based Bayesian reasoning approach for prioritization of failures in FMEA. IEEE Trans. Reliab. 57, 517-528 (2008)
9. Jin, Y.C.: Fuzzy modeling of high-dimensional systems: complexity reduction and interpretability improvement. IEEE Trans. Fuzzy Syst. 2, 212-21 (2000)
10. Tay, K.M., Lim, C.P.: On monotonic sufficient conditions of fuzzy inference systems and their applications. Int. J. Uncertain. Fuzz. 19, 731-757 (2011)
11. Tay, K.M., Lim, C.P.: On the use of fuzzy inference techniques in assessment models: part I— theoretical properties. Fuzzy Optim. Decis. Making 7, 269-281 (2008)
12. Tay, K.M., Lim, C.P.: On the use of fuzzy inference techniques in assessment models: part II: industrial applications. Fuzzy Optim. Decis. Making 7, 283-302 (2008)
13. Yubazaki, N., Yi, J.Q., Hirota, K.: SIRMs (single input rule modules) connected fuzzy inference model. J. Adv. Comput. Intell. 1, 22-29 (1997)
14. Seki, H., Ishii, H., Mizumoto, M.: On the generalization of single input rule modules connected type fuzzy reasoning method. IEEE Trans. Fuzzy Syst. 16, 1180-1187 (2008)
15. Seki, H., Ishii, H., Mizumoto, M.: On the monotonicity of fuzzy-inference method related to T-S inference method. IEEE Trans. Fuzzy Syst. 18, 629-634 (2010)
16. Seki, H., Tay, K.M.: On the monotonicity of fuzzy inference models. J. Adv. Comput. Intell. Intell. Inform. 16, 592-602 (2012)
17. Tay, K.M., Lim, C.P.: Optimization of Gaussian fuzzy membership functions and evaluation of the monotonicity property of Fuzzy Inference Systems. In: IEEE International Conference on Fuzzy Systems, pp. 1219-1224 (2011)
18. Tay, K.M., Lim, C.P., Teh, C.Y., Lau, S.H.: A monotonicity index for the monotone fuzzy modeling problem. In: IEEE International Conference on Fuzzy Systems, pp. 1-8 (2012)