Transforming Public Transport with Predictive Maintenance and EAM

On November 8, the SITCE Congress featured a session focused on the digitalisation of rail and bus operations and maintenance. Notably, Trapeze EAM expert Mika Keskitalo delivered a compelling presentation titled “Predictive Maintenance and EAM for Improved Reliability.”

In his session, Keskitalo illuminated the significance of an integrated asset management ecosystem, highlighting how such systems can be customised to enhance efficiency and reliability for asset owners and maintainers. He emphasised the potential for predictive maintenance strategies to substantially reduce maintenance costs while improving operational reliability and supported the case with a case example of significant efficiency gains, reliability improvements and cost savings achieved from recent projects. 

This session made a significant contribution to the ongoing discourse on digital transformation in public transportation in ASEAN. 

Predictive Maintenance and EAM: A Powerful Partnership 

In today’s fast-paced world, public transportation providers like MATA (Memphis Area Transit Authority) are under immense pressure to deliver reliable service while managing costs and resource constraints. One innovative solution to address these challenges is the integration of predictive maintenance and Enterprise Asset Management (EAM) systems. 

Leveraging AI for Predictive Maintenance 

Condition monitoring has been around for decades, but recent advancements in sensor technology, communication capabilities, and artificial intelligence (AI) have propelled predictive maintenance to new heights. By analysing vast amounts of data from various sensors, AI algorithms can accurately predict potential equipment failures before they occur. 

MATA’s Journey to Improved Reliability 

MATA recognised the potential of predictive maintenance to enhance its bus operations. By partnering with Trapeze and Preteckt, MATA implemented a comprehensive solution that integrated condition monitoring and AI-powered predictive analysis with their Trapeze EAM system. 

Key Benefits of an Integrated Solution 

Implementation of condition monitoring allows organisations to quickly reap some benefits by being able to detect developing faults before they result in a functional failure and by this improve reliability by becoming more pro-active.  

Condition monitoring however does not tell you when the failure is likely to occur. Traditionally this has been the role of senior mechanic or engineer to make an assessment on by when maintenance needs to be applied.  With industry wide shortage of skilled labour and increasing volume of condition data to analyse, this has become an impossible task.  

Building on this with AI assisted fault prediction and machine learning, maintenance organisations can adopt a predictive maintenance approach by automating process of analysing developing faults and optimise their work planning to the most opportune time before there is a failure.

Fig: AI assisted predictive maintenance helps you optimise your work planning. 

Implementation of AI assisted predictive maintenance requires a process of selecting the right predictive models for the asset and training of the machine learning algorithm over a period of time before optimal results are achieved, but published results from an earlier project with MTA illustrate the value of implementing an integrated solution for predictive maintenance with EAM once fully established:

• • Enhanced Efficiency: MATA’s AI-assisted system automates fault reporting and service request generation with high precision resulting in a 50% reduction of time spent on diagnostics.

• • Reduced Costs: The Automated identification of fault and tasks required for rectification allowed MTA to lower spares and material costs by 24%.  

• • Improved Reliability: Optimising work planning with highly accurate fault predictions allowed MTA not only to alleviate constraints related to the availability of skilled labour, but also improve the reliability of their service by reducing the number of road calls (service breakdowns) by 30%. 

The Power of EAM Integration 

Trapeze’s EAM system played a crucial role in the end-to-end solution. By seamlessly integrating with the predictive maintenance system, it allowed for the incorporation of AI technology seamlessly without introducing change to work processes. It enabled efficient work planning and resource allocation, and improved inventory management. This end-to-end approach for automated fault reporting ensures that maintenance activities are optimised and helps MATA achieve their business objectives. 

The combination of predictive maintenance and EAM offers a powerful solution for public transit agencies, whether it be for rail or bus transport. By embracing AI and advanced technologies, organisations can achieve significant improvements in efficiency, reliability, and cost-savings. As the industry continues to evolve, it’s essential to adopt innovative solutions that can be seamlessly integrated into to the existing maintenance processes to further drive operational excellence and passenger satisfaction, without requiring process re-engineering. 

Asset Management as an eco-system 

The Trapeze enterprise asset management system allows you to implement a progressive maintenance practice that combines analysis of fault modes and asset prioritisation to better manage the risks of service interruptions. 

We integrate with technology solutions for real time data monitoring and AI assisted predictive maintenance, as well as tools for root cause analysis of faults. These all enable operators to achieve continuous improvement. 

Trapeze also manage compliance with engineering changes through asset compliance models, campaign work orders for execution of change and continuous monitoring of any non-compliances. 

Our partnership network approach enables the establishment of a fit for purpose tailored eco-system that breaks the silos limiting visibility of important data and automates processes to elevate your asset and maintenance management practices and future proof it to meet the demands of tomorrow. 

For those interested in further understanding the value of an integrated EAM ecosystem, we encourage you to watch our informative video https://trapezegroup.com.my/rail/enterprise-asset-management/#eam-video