Designing Condition-based Maintenance Management Systems for High-Speed Fleet

Abstract

Advancement in the big-data technologies in combination with machine-to-machine (M2M) interconnectivity and predictive analytics is creating new possibilities for real-time analysis of machine components for identifying and avoiding breakdowns in the early stages ahead of time. Designing such a condition-based maintenance system for high-speed fleet requires special attention to the design methodologies used in collecting the operating requirements from the users and translating them into big-data parallel architectures that are capable of exhibiting fault-tolerant behavior and load-balancing possibilities to sustain the real-time data processing demands. This paper discusses the M2M approach for the big-data condition-based maintenance system and the requirement specification steps involved in building such a system, along with the cost-savings benefited from the system.