The implementation of advanced sensor technologies, such as remote condition and monitoring systems, plays a crucial role in improving maintenance practices and reducing downtime in smart railways, highlights, Dr Anirudh Gautam, Principal Executive Director, Resource & Testing Vertical, Research Designs & Standards Organisation (RDSO), Lucknow in an exclusive interaction with Nisha Samant of Elets News Network ( ENN).
How does implementing advanced sensor technologies, such as remote condition monitoring systems, contribute to improving maintenance practices and reducing downtime in smart railways?
At present Indian Railways employs Preventive Maintenance for its assets. In this system, the maintenance is carried out at set intervals irrespective of whether the asset (rolling stock, track, signals, telecommunications, bridge etc.) is in need of maintenance or not. The cost of maintenance of assets on IR is about Rs. 45000 Cr, about 28 per cent of its revenue. The global benchmark is 10%. The only way to reduce the maintenance expenditure on Indian Railways to bring it closer to the Global Benchmark is to move towards Condition Based Maintenance and the adoption of a structured RAMS (Reliability Availability Maintainability and Safety, for condition-based maintenance use of rugged sensors, Artificial Intelligence etc. will be essential.
Can you explain the concept of intelligent traffic management systems in the context of smart railways and their impact on improving train scheduling and congestion management?
Rail Traffic Management Systems (TMS) are systems designed to support managing the inherent complexity of rail services and rail networks by providing an integrated and holistic view of operational performance, enabling rail operational staff to better balance the sometimes competing demands of aspects such as track access and train crew resources when making decisions. Rail Traffic Management Systems support railway operations processes and procedures, and are systems based on the concept of a single, integrated and consistent set of operational data, enabling high levels of rail operations efficiency.
Rail Traffic Management is concerned with the operational and information aspects of running a train service, the timetable or planned headway, the provision of passenger information, the processing of train path requests from different operating companies, the management of delays or routing conflicts, the management of passenger, rolling stock and staff connections etc. Traffic Management includes the systems and telecommunications-based tools used to implement and optimise the plan for that service day with the resources available. Traffic Management is not responsible for the provision of safety, or the safety-signalling layer.
A Railway can be considered to be serviced by three layers, a. Traffic Management Layer, b. Control Layer, c. Safety Layer.
The Traffic Management Layer provides indirect control of Signalling and Trains. It performs the following functions:
- Timetabling
- Customer Information
- Train Data
- Crew Data including Rostering
- Automatic Train Supervision
- Automatic Train Routing
- Interfaces with other Rail Information Systems & Operators
- Wide Area Control
Can you discuss the role of cloud computing and edge computing in smart railway systems, particularly in terms of data processing, storage, and real-time decision-making?
Data from the sensors fitted on different railways assets (moving and stationary) is in the time domain. This data is captured by Data Acquisition Systems and then fed to the Edge boxes which carry out the initial analytics of the time-series data. These analytics may be as simple as a bandpass filter to remove the noise and FFT analysis to transmit only the useful data to the cloud. Edge analytics is used to issue immediate alarms to the operators/ pilots. Further analysis of the data and diagnostics and prognostics are done in the cloud. The results are then transmitted to the users in the form of Dashboards. Users make use of this real-time analysis to take either immediate decisions or long-term decisions. Prognostics and Health Management of Assets cannot be done without the use of edge computing and cloud computing.
Can you provide insights into the key areas of focus within the Resource & Testing Vertical concerning smart railways?
In the Resource & Testing Vertical, RDSO has taken up a project for the implementation of Reliability Availability Maintainability and Safety and PHM for the rolling stock of Indian Railways. Initially, a Proof-of-Concept and Pilot Project is being taken up. This will be followed by larger proliferation. It is also planned to take up similar exercises for Infrastructure like Signals, Tracks, and Bridges although some condition monitoring of the fixed assets is already being done. At present, for the fixed assets only data acquisition and alarms are being generated. Diagnostics and Prognostics are not being done. This will also be taken up.
Also Read | Adapting Train Communication Networks for Diverse Needs
How can smart technologies be utilized to improve the performance, maintenance, and safety of rolling stock in smart railway systems?
Smart technologies will allow the Indian Railways to migrate to Condition Based Maintenance in place of planned or preventive maintenance. Implementation of EN50126 Standard for Reliability Availability Maintainability and Safety will lead to the adoption of Design for Reliability and Safety to be introduced during the concept and design phase of rolling stock.
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