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While the risks associated with changing a tried-and-true formula weigh heavily on the minds of those responsible, the upside is that the highly complex nature of rail networks and systems allow for the opportunity to innovate and leverage technology to change the way rail networks do business.
Many owner-operators around the world have recognized the potential for digital twins in their work and have begun to explore the opportunities for applying big data analytics, artificial intelligence (AI), and machine learning (ML) throughout the design, construction, operation, and maintenance of rail and transit networks.
What Is a Digital Twin?
A digital twin is a digital representation of a physical asset, process, or system, as well as the engineering information that allows us to understand and model its performance. Plainly stated, a digital twin is a highly detailed digital model that is the counterpart (or twin) of a physical asset. That asset might be anything from a ticket machine or escalator in a station, through track and the switches and crossings within it, to related infrastructure like overpasses or overhead line structures, right up to and including an entire city.
Connected devices and sensors on the physical asset collect data that might relate to condition or performance that can be mapped onto the digital twin to understand how the physical asset is performing in the real world, but also, through analysis or simulation, how it might perform in the future or with a different set of parameters.
Why Are Digital Twins Important?
Digital twin technology has existed in industries like manufacturing for many years, driving lean processes, improving performance, and predicting and highlighting components at risk of failure. Additionally, digital twin technology ensures that the lessons learned contribute to design enhancement and are applied to future products and systems. The relevance and influence of digital twins, which span the entire asset lifecycle, are significant when applied to rail infrastructure.
During the planning, design, and construction of a new railway or major upgrade, project digital twins can enable the optimization of design in line with operational requirements and reduce the risk of delayed or nonconformant construction through simulation. Project digital twins can also improve logistics and communication within the supply chain, which can help maintain the schedule and budget.
During operations, performance digital twins become the most valuable. Owner-operators gain insight when inputs from Internet of Things (IoT) connected devices, such as drones that deliver continuous surveys to provide real-time tracking of asset changes in real-world conditions, add to the digital representation. This transparency helps owner-operators prioritize and improve maintenance or upgrades.
Consequently, the most significant value a rail or transit system can achieve is through the successful implementation of digital twin technology. By using digital twins to plan, design, and build the network, and utilizing the digital twin during operations, a rail or transit owner-operator will improve performance and reliability.
With the application of AI and ML, analytics visibility gained from big data can provide insight and immersive digital operations to enhance the effectiveness of operations and maintenance. In this instance, access to performance digital twins might enable staff to anticipate and avoid issues before they arise or improve reaction times to system failures to reduced downtime.
With the application of drones and robots, plus AI-based computer vision, automating inspection tasks via a digital twin experts can conduct inspections remotely, increase productivity, leveraging the value of specialists, and reducing the risk of exposing team members to dangerous environments.
Realizing the Potential of Digital Twins
There must be practical solutions for the synchronization of the physical asset’s changing condition to realize the full potential of digital twins. The timing and scope of this synchronization is key because certain assets update in near real-time, which can be critical to their reliability. For others, a weekly, monthly, or even annual update on condition may be sufficient. Therefore, it is important that the organizations and professionals involved have a clear strategy when setting the criteria for synchronization, including which assets should be analyzed, when, and by what parameters.
However, merely capturing and representing physical conditions, including IoT inputs, can never be sufficient enough to understand, analyze, or model intended improvements, without also comprehending the digital engineering information used in the project’s or asset’s engineering design and specification.
Digital engineering information is like the “digital DNA” for infrastructure assets. Just as doctors can analyze human DNA to anticipate health issues and personalize care for better health outcomes, project delivery firms can harness digital engineering information to enable collaboration, improve decision making, and deliver better project outcomes.
For owners, leveraging “digital DNA” is all about creating and using digital twins to their full advantage—personalizing asset maintenance and maximizing asset reliability and uptime. It is about creating an open, connected data environment® (CDE) that provides trusted information wherever and whenever it is needed to help design, build, operate, and maintain physical assets. Then, owners will use digital twins to make better decisions, gain more efficiency, and improve performance.
Current Networks are the Digital Twins for Future Projects
Bentley sees its users advancing digital workflows and using intelligent components, and digital context to improve project delivery and/or enable assets to perform better, every day and all around the world. One organization achieving these objectives is Maharashtra Metro (Maha Metro) in Nagpur, India.
Maha Metro’s implementation of Bentley’s OpenRail solution uses iModels as its final delivery format due to their ability to provide reliable, long-lasting asset models for reference. The organization is committed to a full lifecycle approach and has deployed a digital project delivery system with OpenRail’s connected data environment (CDE) at its core and encompassing every phase of the asset lifecycle from planning to performance.
Maha Metro’s CDE is configured to record all data and uses asset tags to link components created with Bentley’s open modeling applications, such as its enterprise resource planning system. Hundreds of thousands of drawings and documents are transacted among approximately 400 users within the CDE currently, providing real-time access to trusted information wherever and whenever it is needed. The expansive CDE also provides data mobility to close communication gaps, speed up design issue resolution and approvals, and achieve millions of US dollars in cost savings.
The digital DNA Maha Metro and its supply chain is creating during design and construction will allow the organization to manage current, future, and refurbished assets. By ensuring this trusted information remains current and accessible, the organization’s system will enable strategic decision making, establish condition-based monitoring, and progress toward predictive maintenance strategies that are expected to save at least USD 222 million over 25 years of the railway’s operational life.
It is clear that digital twins are gaining momentum, particularly within organizations that presently have IoT initiatives. The emergent nature of digital twins will require an approach with clear business objectives and an agile approach to experiment and learn from experiences. Just as Maha Metro is setting the agenda and direction for the industry, we at Bentley fully expect to see the use and adoption of digital twins become common place within rail owners and their supply chains.
The post Realizing the Potential for Digital Twins in Rail appeared first on Railway Age.
This article first appeared on www.railwayage.com
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