Abstract
In the past, railway systems were overdesigned and underutilized making the need for effective, coordinated, and optimized maintenance planning non-existence. With passing years, these assets are getting old and at the same time, their utilization has increased manifold mainly due to societal consciousness about climate and cost. With steeply increasing utilization of railway systems, the major challenge is to find the time slot to perform maintenance on the infrastructure and rolling stocks to maintain its functionality and ensure safe train operation. This has led the sector to look for new and emerging technologies that will facilitate effective and efficient railway maintenance and ensure reliable, punctual, and safe train operation. This chapter presents the current status and the state-of-the-art of maintenance in railway sector transformative maintenance technologies and business solutions for the railway assets. It discusses the digital transformation of railway maintenance, application of artificial intelligence (AI), machine learning, big data analytics, digital twins, robots, and drones as part of the digital railway maintenance solutions. The chapter presents a conceptual road map for developing transformative maintenance solutions for railway using new and enabling technologies which are founded on data-driven decisions.
| Original language | English |
|---|---|
| Title of host publication | Handbook of Advanced Performability Engineering |
| Publisher | Springer International Publishing |
| Pages | 565-595 |
| Number of pages | 31 |
| ISBN (Electronic) | 9783030557324 |
| ISBN (Print) | 9783030557317 |
| DOIs | |
| Publication status | Published - 16 Nov 2020 |
| Externally published | Yes |
Keywords
- AI
- Augmented reliability
- Big data
- Digital twin
- IIoT
- Machine learning
- Maintenance
- Maintenance analytics
- Railway assets
- Transformative technologies