Integrating Cost into Rail Wheel Maintenance

Abstract

The rapid advancement of Information and Communication Technologies (ICT), sensory technologies, and the integration of advanced big data analytics into industrial entities has brought both opportunities and challenges. The companies are facing challenges in the new competitive business environment in dealing with big data issues for rapid decision making, improved productivity, and sustainable value chain services. U.S. has been driving the Cyber Physical Systems (CPS), Industrial Internet, and Advanced Manufacturing Partnership (AMP) Program to advance future manufacturing. Germany is leading a transformation toward 4th Generation Industrial Revolution (Industry 4.0) based on Cyber-Physical Production System (CPPS). China has just launched 2025 Plan and Internet Plus to strengthen manufacturing and accelerate service innovation. It is a clear trend that as more predictive analytics software and embedded IoT are integrated in industrial products and systems, predictive technologies can further intertwine intelligent algorithms with electronics and tether-free intelligence to predict product performance degradation and autonomously manage and optimize product service needs. This paper will address the trends of big data analytics and cyber-physical systems for prognostics and health management (PHM) of future railway transportation systems. First, the systematic 5C architecture for CPS-enabled intelligent operation and maintenance (O&M) is discussed. Then a description of analytical tools and technical concepts in CPS is presented with case studies is presented. And finally, the benefits, future trend, and challenges for CPS applications in railway systems are concluded.