Rail industry news (Australia, New Zealand)

Data driven longevity

Siemens Mobility delivered AI-powered data analytics for Singapore’s Downtown Line, to optimise asset lifecycle management and drive sustainability. 

How do railway operators achieve high reliability and efficiency at optimal cost while ensuring sustainability? The answer lies in harnessing deep railway domain knowledge and the power of Artificial Intelligence (AI). This helps analyse critical data that enables the most cost-effective maintenance regimes and provides accurate prediction of potential events for necessary interventive measures to be taken.

Introducing Digital Asset Management for Rail Systems (DAMfRS), an innovative AI-driven product crafted by Siemens Mobility to meet these needs. DAMfRS serves as its digital services solution, tailored to empower railway asset owners, maintainers, and operators in making informed decisions that drive the maximum value from their asset portfolio. 

Rooted in robust asset management principles aligned with ISO 55001 standards, this product draws upon asset and system data, and utilises Siemens’ domain expertise to fulfill its overarching mission: optimising whole life cost by enhancing reliability, availability, maintenance efficiency, inventory optimisation and renewal forecasting.

Success Story – Singapore implementation of DAMfRS

The Rail Enterprise Asset Management (REAMS) project in Singapore marked a milestone as the inaugural implementation of DAMfRS by Siemens Mobility. 

Tailored to meet the unique requirements of the customer, this bespoke DAMfRS solution is recognised as a pivotal facilitator in realising the nation’s ambitious long-term transport and sustainability objectives. Aligned with Singapore’s Green Plan for 2030 and Land Transport Master Plan 2040, the overarching aim is to achieve a 75 per cent mass public transportation peak-period modal share, which also includes expanding Singapore’s rail network by 130 kilometres and deliver a convenient, well-connected, inclusive, and fast land transportation system.

To deliver the project, a dedicated team from Siemens Mobility worked closely with the customer, the Land Transport Authority (LTA) of Singapore to implement REAMS for the Downtown Line (DTL) – a driverless metro line comprising 34 stations, 42 kilometres of track and 92 metro trains.

The Siemens Mobility team covered the data value chain by extracting, processing, developing analytics algorithms and crafting telling visualisations from a range of customer data sources including:

  • rail assets trains, signaling system, and platform screen doors, providing system specific event and diagnostic data;
  • the Centralised Maintenance Management System (CMMS) that contains work planning, scheduling, assignment, and execution records of day-to-day maintenance operations; and

    The systems can be moulded to fit the needs of any transport organisation. IMAGES: Siemens Mobility
  • the Enterprise Resource Planning (ERP)system that contains the financial, costing and purchasing details of the assets within scope.

Capitalising on the high volumes of system, diagnostics, operational and financial data from multiple assets, the REAMS solution offered the customer timely alerts on the health statuses of its assets and insights on the long-term performance and costs aspects. This contributed to higher daily system availability, and greater appreciation of the anticipated total cost of ownership. The customer was able to utilise the solution output to execute immediate improvements to maintenance regimes and prepare adequately for capital intensive asset renewal activities in the coming years.

The head of digital services Asia Pacific for Siemens Mobility, Lester Lim, shared some details on the project and explained how Siemens worked closely with the LTA for a tailor-made solution.

“This project saw Siemens Mobility work in close collaboration with the customer, LTA, and our valuable local partner, ST Engineering Urban Solutions (previously known as ST Engineering Electronics, STE), to co-develop and implement REAMS for selected Downtown Line assets,” he said.

“It was important that we worked closely with the customer and the operator of DTL, SBS Transit (SBST), to obtain the required data to deliver lifecycle intelligence and decision support to achieve a balance between short- and long-term sustainability.

“We led workshops with key stakeholders to progressively identify software requirements that would allow the customer to achieve their operational and asset management objectives. We conducted thorough data assessment exercises and also led the implementation of pilot run trials to validate the maintenance regime recommendations put forth by the REAMS algorithms. We are happy to report that the customer is confidently pursuing fleet-wide regime changes.”

Ultimately, Siemens and the customer have achieved:

  • integration and management of the performance and cost characteristics of the DTL line in a centralised digital rail asset management platform;
  • managed limitation of system downtime for the maintenance of rolling stock and signaling systems; and
  • improvements to system and asset performance over the lifecycle

Following the successful completion and system acceptance of the REAMS project, the system is currently used by SBST and maintained by Siemens Mobility’s consortium partner STE.

Bringing AI-driven Digital Asset Management for Rail System (DAMfRS) to Australia and New Zealand

Growth in the Australian and New Zealand rail industry is forecast to continue in the coming years, to enhance connectivity and support sustainable transportation to help reach net zero. 

With the recent record level of investment in the rail networks across Australia and New Zealand, the need for robust digital asset management solutions is paramount. The scale and complexity of these railway projects necessitate advanced technological solutions to ensure optimal reliability, safety, and efficiency. 

Much like its success in Singapore, DAMfRS holds immense potential to deliver substantial benefits in Australia and New Zealand. Through real-time asset status monitoring, maintenance optimisation analysis, inventory holding right-sizing recommendations, and data-driven asset renewal decision-making, rail owners, maintainers, and operators can maximise returns on investment, minimise downtime, and safeguard the longevity of expanded rail infrastructure.

The question then arises: How do we embark on this journey? 

“You start by embracing the Siemens Mobility Railigent X platform,” suggests Lim.

The Railigent X platform serves as a central hub for all railway community stakeholders seeking digital solutions to enhance their services and products.

Siemens’ experience and expertise in railway design, construction, operations, maintenance and AI-led data analytics offers an opportunity to develop digital solutions to address operational, maintenance, and strategic asset management needs. Siemens’ suite of in-house and partner-developed applications available on the Railigent X platform provides flexibility, enabling the activation of additional applications as needed in the future.

By consolidating data and user needs efficiently, the need for costly overheads associated with purchasing discrete
software programs is eliminated. In essence, Siemens serves as the singular supplier for all current and future railway data and analytics requirements.

“The Railigent X data platform and analytics engines are not limited to Siemens products but can seamlessly integrate with other products as well,” Lim said. This openness, facilitated through APIs (Application Programming Interfaces), allows customers and partners to share and utilise generated data for various use cases while upholding rail safety and cybersecurity standards. Customers can effortlessly adopt Siemens’ digital offerings uniformly across all their lines, irrespective of the manufacturer, enabling them to extract value and synergies from the entire network.

This ecosystem approach to harnessing value from AI-driven data analytics, combined with deep domain expertise, has the potential to optimise operational capabilities, maintenance strategies, and the total cost of ownership, ultimately benefiting railway organisations and passengers alike in the Australian and New Zealand markets.