Predictive Maintenance Planning With Fuzzy Neural ... - AMMJ

More documents

Recommendations

Info

1113Not inspection1133Not inspection1148inspection1158inspection1167inspection1114Not inspection1134inspection1149inspection1158inspection1167inspection1115Not inspection1135Not inspection1149inspection1159inspection1168inspection1116Not inspection1136inspection1150inspection1159Not inspection1169inspection1117inspection1137Not inspection1150inspection1160Not inspection1170inspection1118Not inspection1151inspection1171Not inspection1119Not inspection1151Not inspection1172Not inspection5. ConclusionIn this study, we have designed a hybrid model analytic network process (ANP) and fuzzy neuralnetworks to control and predict Failure times. For this purpose, we studied 6 Factors influencing moldmanufacturing faults. Then, using the analytic network process, number of criteria was reduced from 6to 3 series. After calculating the period of disability the network analysis of the output of the networkwas considered as input variables of fuzzy neural networks. Using fuzzy neural networks, The resultswere compared with the case of fixed time frames based on 15-day, The results show that the fuzzyneural network prediction model, have Reduced inspection costs by 25% being compared to the sametime of inspection Therefore, using this model we can also avoid the drawbacks of sequential faultslead to Stop in providing the services, the risk of explosion, and the dangers of life, significantly reducethe costs of inspection.References[ 1] A. Borden, “Designing and Maintaining Decision-making Processes”. AGARD ConferenceProceedings, Paris, France, 1993[ 2] A. Hurson, S. Pakzad, B. Lin, “Automated Knowledge Acquisition in a Neural Network BasedDecision Support System for Incomplete Database System”. Microcomputers in CivilEngineering, Vol. 9, No. 2, 1994.[ 3] Bansal D. Evans D. Jones B, (2006) Bjest: A reverse algorithm for the real-time predictivemaintenance system, International journal of machine tools & Manufacture; (46) 1068-1078.[ 4] Bansal D. Evansb DJ. Jones B, (2005) Application of a real-time predictive maintenance system toa production machine system .J Machine tools and manufacture; 1210- 1221.[ 5] Becraft WR. Lee P L, (1993) an integrated neural network/expert system approach for faultdiagnosis.J Computers and Chemical Engineering; 1001-1014.[ 6] C. Kocourek, “A Petri-net based Design Decision Support System”. Proceedings of the IASTEDInternational Conference, Applied Modeling and Simulation, Vancouver, BC, Canada, 1993, 108-114.[ 7] F. Kong, R. Chen, “A Combined Method for Triplex Pump Fault Diagnosis Based on WaveletTransform, Fuzzy Logic and Neuro-Networks”. Mechanical Systems and Signal Processing, Vol.18, 2004, 161-168.[ 8] He Z. Wu M. Gong B, (1992) neural network and its application on machinery fault diagnostics.IEEE International Conference on Systems Engineering; 576-579.[ 9] J. Coutaz, G. Calvary, A. Demeure, Li. Balme, S. Lavirotte, G. Rey, and J.Tigli Infrastructure andArchitectural Principles for Plastic User Interfaces , Proceedings of the 2012 Workshop onAmbient Intelligence Infrastructures (WAMII),P 31-34[ 10] J. Jang, 1993 “ANFIS: adaptive-network-based fuzzy inference system”. IEEE Transactions onSystems, Man and Cybernetics, Vol. 23, 1993, 665-685.[ 11] Javadpour R.Knapp GM, (2003) A fuzzy neural network approach to machine conditionmonitoring .J Computers and industrial engineering; 323-330
[ 12] Kim Yong Seog, (2004), an intelligent system for customer targeting: a data mining approach .JDecision Support Systems; 215-228.[ 13] Knapp G M. Javadpour R. Wang HP, (2000) An ARTMAP neural network-based machinecondition monitoring system. J Quality in Maintenance Engineering; 86-105.[ 14] Knapp GM. Wang HP, (1992) Machine fault classification: A neural network approach. JProduction Research; 811-823.[ 15] L. Tong, Y. Liang, “Forecasting Field Failure Data for Repairable Systems Using NeuralNetworks and SARIMA Model”. International Journal of Quality and Reliability Management,Vol. 22, No. 4, 2005, 410-420.[ 16] Lucifredi A. Mazzieri C. Mrossi, (2000) Application of Multi regressive Linear models, dynamickriging models and neural network models to predictive maintenance of Hydroelectric powersystems, Mechanical systems and signal processing; 14(3), 471-494.[ 17] Mitra S. Pal S K, (1995) Fuzzy multi-layer perception, inferencing and rule generation. IEEETransaction on Neural Networks; 51-63.[ 18] Molina J.M. Isasi P. Berlanga A. Sanchis A, (2000) Hydroelectric power plant managementrelying on neural networks and expert system integration, Engineering Applications of ArtificialIntelligence; 13, 357-369.[ 19] O. Castillo, P. Melin, “A Hybrid Fuzzy Fractal Approach for Time Series Analysis and PlantMonitoring”. International Journal of Intelligent Systems, Vol. 17, 2002, 751-765.[ 20] P. Thyregod. , “Modeling And Monitoring In Injection Molding” .Dissertation 2001, QS StatisticsDepartment, Novo Nordisk A/S IMM-PHD-2001-80 ATV Erhvervsforskerprojekt EF 695[ 21] R. Yam, P. Tse, L.Li, P. Tu, “Intelligent Predictive Decision Support System for Condition-BasedMaintenance”.International Journal of Advanced Manufacturing Technology, Vol. 17, 2001,383-391[ 22] Spearman C, (1904) General intelligence: objectively determined and measured, American Journalof Psychology; (15) 92-201.[ 23] Swanson l, (2001) Linking maintenance Strategies to performance. J Production economic; 237-244.[ 24] T. Quah, C. Tan, T. Srinivasan, “Fuzzy-neural-network Decision Support Systems. Proceedings ofInternational Symposium on Artificial Intelligence, The Artificial Intelligence TechnologyTransfer Conference, Monterrey, Mexico, 1993.[ 25] Wilson ID. Paris SD. Ware JA. Jenkins DH, (2002) Residential property price time seriesforecasting with neural networks, Knowledge-based systems; 335-341.[ 26] Wittkemper H.Steiner M, (1996) Using neural networks to forecast the systematic risk of stocks. JEuropean Journal of Operational research; 577-588.
Page 1 and 2: Predictive Maintenance Planning Wit
Page 3: In another trial, Bansal et al have

Predictive Maintenance Planning With Fuzzy Neural ... - AMMJ

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?