Digital twins are nothing new, but artificial intelligence is augmenting their capabilities. Together they are changing the way products are designed, manufactured and maintained. The combination of these technologies provides a forensic perspective into our increasingly complex and interconnected world.
By deploying digital twins and artificial intelligence, organizations can gain granular insights into their operations, enabling them to reap significant benefits in cost savings, increased efficiency, and improved sustainability. Product quality is also improved by reducing defects and accelerating problem resolution throughout the life cycle. Furthermore, innovation increases through more frequent and comprehensive development.
Gartner defines a digital twin as “a digital representation of a real-world entity or system.” Data from multiple digital twins can be aggregated to form a composite view across multiple real-world entities, such as a power plant or a city, and their associated processes. "Artificial intelligence augments digital twins, allowing the technology to observe what-if scenarios and run simulations, providing insights previously unavailable. This improved cause-and-effect situational awareness supports more agile and sustainable decision-making.
Digital twins not only help optimize operations; they play a role in helping organizations achieve their environmental, social and governance (ESG) goals plays a key role. CapGemini’s research found that 57% of organizations believe digital twin technology is critical to improving sustainability efforts. Digital twins provide a way to model and understand how to reduce energy consumption and emissions so that organizations can test scenarios to meet sustainability and climate goals. As sustainability becomes a global imperative, this will accelerate adoption, especially as artificial intelligence is increasingly used to enhance digital twins.
As cities strive to reduce their impact on the environment, digital twins and artificial intelligence will play a vital role. Together, the two can create a virtual simulation , helping planners understand how to reduce congestion, emissions, pollution and other challenges by analyzing data from different sources and testing different variables in virtual models.
Pioneers to adopt this approach The city is Las Vegas, which uses this technology to simulate future energy demand, emissions, parking, traffic and emergency management. IoT sensors collect data from cars, charging networks and municipal infrastructure for modeling and scenarios planning. City officials will use the insights gathered to inform ESG policies and priorities.
As more cities around the world work toward carbon neutrality, digital twins and artificial intelligence provide a way to model and process large amounts of data from different sources, allowing municipalities to fully understand how different decisions and policies will affect strategic climate goals.
In industrial settings, digital twins provide manufacturers with a way to understand how to optimize operations and improve sustainability. For example, simulations can identify potential Pain points, highlighting where energy losses occur, and highlighting opportunities to reduce consumption. Artificial intelligence algorithms can process data, identify patterns and predict future outcomes far beyond human cognitive capabilities. In addition, virtual simulations reduce the complexity associated with building physical Prototype-related waste and power consumption.
By creating a simulation of the production line, manufacturers can understand how to make changes at each stage to reduce environmental impact and increase efficiency, resulting in savings Cost. Unilever tested these technologies at one plant and realized $2.8 million in savings through reduced energy consumption and increased productivity.
These are just a few examples, highlighting Learn how artificial intelligence and digital twins are ushering in a new era of smart manufacturing.
Another area where digital twins are helping with sustainable development is about creating smart buildings. With increasing regulations aimed at designing greener buildings, the construction industry needs an approach to program planning that reduces environmental impact and minimizes energy consumption before any groundbreaking.
Digital models enable infrastructure owners to better utilize resources, meet human needs, and make decisions that support a more sustainable built environment. By leveraging data from various sources, resources can be better planned. Accenture estimates that using digital twin technology, a building's energy consumption can be reduced by 30% to 80%.
As digital twins are adopted and smart technologies become more prevalent, better decisions will be made to support a more circular, less carbon-intensive economy, ultimately creating A more sustainable planet.
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