The industry is buzzing right now about the “digital twin” – ARC, Gartner and LNS have all recognized the technology’s potential to transform asset design, construction, operations and maintenance. Applying the digital twin to a single asset is only the beginning, as socializing the digital twin concept across a fleet of assets enables twin-to-twin assessments for optimized operations.
What is a digital twin?
The digital twin is a complete virtual representation of a piece of equipment, combining design, asset and process data in a complex model. A digital twin is much more than a static picture – it applies advanced analytics to that data to provide a complete understanding of the asset. As the lifecycle continues and more data is fed into the twin, the model continues to evolve alongside the asset, getting smarter and smarter. The twin is socialized across the enterprise, providing increased access to relevant information across the decision-making chain and enabling collaboration of people, processes and equipment.
This concept has incredibly powerful applications across the asset lifecycle. At the design and construction stage, the concept of the first-born digital twin allows engineers to test the twin of an asset before it is even constructed. In the operational phase, the volume of data collected, contextualized and analyzed allows deeper insight into key performance drivers, enabling improved asset performance and reliability. This concept provides similar benefits during maintenance, allowing users to access the twin to compare the current operating state to original design specifications, increasing operational knowledge and facilitating repair. As part of the digital twin, predictive analytics identify and diagnose issues before they occur, facilitating the switch to a proactive maintenance model for improved asset performance and reliability.
The power of the digital fleet
The digital twin concept is dramatically amplified when applied across an entire fleet of assets – the digital fleet. Using the digital fleet concept, deep twin-to-twin comparisons can be applied to similar assets regardless of location, manufacturer or other variables. The increased volume of data enhances the accuracy of the model’s analytics, allowing the twin to evolve based on fleet-wide experiences, making every model smarter as more and more equipment is connected. These comparisons help identify commonalities across highest or lowest performing assets, for potentially business-changing key performance insights and opportunities to improve operations and maintenance.
Future discoveries may lead to completely autonomous assets or entire fleets of assets operating autonomously and continually learning and acting without human intervention to improve performance, reliability and availability.
Want to get started with your digital fleet journey? Learn more about how our Enterprise APM solutions enable the digital twin for improved asset performance and reliability.
6 years ago
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