The Railway Industry has prized consistency, but the digital revolution is changing everything. Gone are the days of slow and steady improvements in efficiency – now, Railway Networks need to be able to respond quickly to changing demands from an ever-growing and demanding population. Passenger and freight flexibility drive ever more demanding timetabling and infrastructure maintenance requirements.
Digital Technologies are already demonstrating how Railway Networks can get more out of less through innovations such as Big Data, Artificial Intelligence and Digital Twins. These innovations enable advanced analytics services to support condition-based maintenance. Coupled with cloud computing, predictive maintenance will yield the next big efficiency leap – preventing failures, cutting out unnecessary interventions and, ultimately driving up asset capacity for railway customers.
Railroads must improve their efficiency while simultaneously lowering costs. Digital technologies can facilitate the transition but must be implemented effectively or risk being an expensive white elephant.
The concept of the revolution for railways is straightforward: “use new technologies to automate or improve existing tasks and processes to increase safety, improve reliability and increase efficiency”. But the sheer size and complexity of railways means that transitioning from traditional engineering processes to digital first can be costly, and immensely time-consuming.
The opportunities already exist though to make dramatic improvements to railways engineering delivery. Networks now have access to new technologies platforms like Cordel, which provide end-to-end Big Data and Inspection Automation services using AI. Railway companies are able to use these platforms to connect with the latest sensors (IoT and remote sensing), data acquisition devices, big data management services and Artificial Intelligence capabilities. The Big Data AI platforms help Railway Networks to manage the increasing volume of high-quality raw data from sensors in the field – and convert it into actionable output, turning new technology concepts into railway reality.
6 Digital insights impacting the world’s railways
We’ve identified six digital insights disrupting the world’s railways:
- The profusion (and increasing affordability) of sensors and advanced analytics is making condition-based maintenance an attractive lever for increasing maintenance efficiency.
- The next big leap forward from condition-based to predictive maintenance requires further investment, not least in fundamental understanding of the underlying railway science.
- People Roles in the new maintenance ecosystem will shift away from inspection (that will be automated) and towards analysis and rectification (utilising skills and increasing job satisfaction).
- The railway industry will attract a healthy mix of new entrants (like technology companies and start-ups) alongside traditional service providers as they transition towards proving more digitised services and solutions.
- Data sharing is crucial in an increasingly complex data landscape that requires careful IT architecture to build-in the appropriate cyber-security. Importantly, to optimise the power of their data and encourage innovation, railways need to ensure common and open data standards across disciplines. Railways should strive to irradicate proprietary formats because although they may masquerade cyber-security, in reality they impose spurious technical and commercial constraints.
- The time is now for railways to embrace the opportunities provided by new digital technologies. Automated inspection and focused condition-based maintenance is already starting to deliver the positive disruption that is key to maintaining competitiveness and performance for the world’s railways.
Using digital innovations to accelerate the path towards condition-based maintenance
Railway Operations are also seeing the effect of this revolution in digital technologies – it’s not all about sensor data and analytics though! Railway companies are now looking to Artificial Intelligence (AI) as an enabler for more efficient Railway Operations through condition-based maintenance alternatively named ‘risk-based inspections’.
The problem is not made up of just one discreet component though, enabling a pathway to condition-based maintenance is multi-faceted, different IT disciplines, different railway engineering disciplines, politics, progress and the always scary process of change.
We have identified five high-level recommendations or observations that could assist rail operators, technology providers, services and advisors on the journey through digital disruption.
- The need to define desired strategic target state and develop the eco-system to support that objective. As assessment along key parameters such as network type, density, population, age, size, timetables and historical, budgets and target timelines can help railways to understand the ideal future position
- Success in the new maintenance and inspection scheme is all about data. Data from sensors across the network. Which party owns what kind of data, what are the data standards (if any), is it founded on open or proprietary data standards, and what or who is going to do what with what data.
- The eco-system made up of the networks, train operators, finance companies, technology companies and service providers need to find a way to effectively couple and co-locate rail engineering expert knowledge and the expertise in modern big data analytics to develop the new analytic and data sharing modules.
- In order to realise the impact, the entire value chain in maintenance and inspections needs to be addressed; equipping locomotives with sensors, data standards and definition, engineering discipline alignment all need to be addressed.
- A specific application within a specific discipline or a component-by-component rollout of condition-based or predictive based maintenance should be pursued only for business-case positive components.
Railway operators should look at the overall Railway Assets and their performance as a system rather than taking an isolated component-by-component approach.
A new, more fleet-wide / network-wide maintenance concept will require new skills in railways – railway engineers need to develop competencies that are not traditionally found within Railway Engineers. Railway operations and maintenance are also going to face a big challenge in coping with the new digital world as they will have to learn how to operate Railway Assets under non-traditional conditions, where parts of the Railway Asset do not work due to smart components or smart sensors being out of service.
The need for Railway Operators and Engineers – who might be unfamiliar or uncomfortable with data-driven decision making, to learn how to cope with a Railway Asset that is not performing at its full potential due to some digital technology being out of service or malfunctioning.
Digital technologies are already demonstrating how railway networks can get more out of less and the railways should be prepared for what comes next – disruption from within based on new sensors, new technologies and new data paradigms.
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