Infrastructure is the most important and costliest component of any transportation system. Proper maintenance of these physical assets is an utmost necessity for success of any transportation system. So, a policy driven approach is taken for maintaining these physical assets effectively throughout their lifecycle. This is called Transportation Asset Management. There are few guiding principles to formulate any Transportation Asset Management program. Those are as follows.
There are a set well-defined goals and objectives for any transportation asset management program. Resources are allocated to different schemes to achieve these goals.
Before allocating funds to any scheme, it is advisable to analyze how different allocations will impact achievement of relevant policy objectives/goals.
The merits of different options with respect to any goal are evaluated using credible and current data. For example, should one go for Preventive Maintenance or Predictive Maintenance based on say overall cost, how effective both have been in past etc.
Performance/results of any scheme is monitored and reported for both impacts and effectiveness.
From these principles we can conclude that it is a program that optimizes the performance and cost-effectiveness of transportation facilities. One way of doing that is keeping the infrastructure in as good or better condition than it is now in lowest cost possible. This can be done through an Asset Performance Management program which involves different type of maintenance strategies.
The prevalent approach is to schedule maintenance at regular intervals. This is called Preventive Maintenance. It is costly and requires a lot of resources. But with the advent of sensor, IIoT and cloud technologies, now the actual condition can be monitored continuously and maintenances can be done when truly needed. This is called Predictive Maintenance (PdM). It is much more efficient and hence more cost-effective as well.
Now, let’s see a scenario how PdM can help in asset performance management. Trains are one of the major constituent in any public transportation system. Maintenance of railway infrastructure (rolling stocks to be particular) is one of the most cumbersome and costly affair. The best solution available as of now for the same is preventive maintenance which is costly and resource consuming. But, we are well aware that one of the signature characteristics of any rolling element is vibration pattern associated with it. Depending on the working condition, this vibration pattern changes significantly. With an accelerometer sensor this vibration can be measured and monitored in a real-time basis. Similarly, the temperature and lubrication can also be monitored on a real-time basis. Using these data a predictive maintenance tool can be built, which can monitor the rolling stock data and alert when the system requires any maintenance.
For this, the deployment cost can be a bit higher. But, over a longer timeframe, this can reduce maintenance cost by 40% compared to preventive maintenance. So, this serves the purpose of better resource allocation and cost optimization. Also, this is a completely data driven process. Therefore, it provides a better avenue to measure performance and overall effectiveness as well as increases accountability. So, it is high time for public transport operators to utilize predictive maintenance as a strategic tool in their asset management program.
Author: Himansu Sahu, Business Analyst, Digital Transformation Services
Sasken is a specialist in Product Engineering and Digital Transformation providing concept-to-market, chip-to-cognition R&D services to global leaders in Semiconductor, Automotive, Industrials, Smart Devices & Wearables, Enterprise Grade Devices, Satcom and Transportation industries.
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