A study on reliability centered maintenance planning of a standard electric motor unit subsystem using computational techniques

The design and manufacture of urban transportation applications has been necessarily complicated in order to improve its safety. Urban transportation systems have complex structures that consist of various electric, electronic, and mechanical components, and the maintenance costs generally take up approximately 60% of the total operational costs. Therefore, it is essential to establish a maintenance plan that takes into account both safety and cost. In considering safety and cost limitations, this research introduces an advanced reliability centered maintenance (RCM) planning method using computational techniques, and applies the method to a standard electric motor unit (EMU) subsystem. First, this research devises a maintenance cost function that can reflect the current operating conditions, and maintenance characteristics, of components by generating essential cost factors. Second, a reliability growth analysis (RGA) is performed, using the Army Material Systems Analysis Activity (AMSAA) model, to estimate reliability indexes such as failure rate, and mean time between failures (MTBF), of a standard EMU subsystem, and each individual component Third, two optimization processes are performed to ascertain the optimal maintenance reliability of each component in the standard EMU subsystem. Finally, this research presents the maintenance time of each component based on the optimal maintenance reliability provided by optimization processesand reliability indexes provided by the RGA method.

[1]  J. Moubray Reliability-Centered Maintenance , 1991 .

[2]  Geoffrey E. Hinton,et al.  Learning internal representations by error propagation , 1986 .

[3]  Anthony M. Smith,et al.  Reliability-Centered Maintenance , 1992 .

[4]  W. Vent,et al.  Rechenberg, Ingo, Evolutionsstrategie — Optimierung technischer Systeme nach Prinzipien der biologischen Evolution. 170 S. mit 36 Abb. Frommann‐Holzboog‐Verlag. Stuttgart 1973. Broschiert , 1975 .

[5]  Lawrence J. Fogel,et al.  Artificial Intelligence through Simulated Evolution , 1966 .

[6]  Richard B. Jones Risk-based management : a reliability-centered approach , 1995 .

[7]  Ronald C. Suich Reliability and cost: Questions for the engineer , 1997 .

[8]  Felix Schmid,et al.  A reliability centered approach to remote condition monitoring. A railway points case study , 2003, Reliab. Eng. Syst. Saf..

[9]  Ingo Rechenberg,et al.  Evolutionsstrategie : Optimierung technischer Systeme nach Prinzipien der biologischen Evolution , 1973 .

[10]  Christian Lebiere,et al.  The Cascade-Correlation Learning Architecture , 1989, NIPS.

[11]  K. S. Jacobs Reducing Maintenance Workload Through Reliability‐Centered Maintenance (RCM) , 1998 .

[12]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[13]  Adamantios Mettas,et al.  Reliability allocation and optimization for complex systems , 2000, Annual Reliability and Maintainability Symposium. 2000 Proceedings. International Symposium on Product Quality and Integrity (Cat. No.00CH37055).