A digital twin is a virtual representation of a physical object, process, or system. It uses simulation and real-time data to help predict outcomes and enhance decision-making. A digital twin can be a replica of anything. It can be small and simple like a microchip or big and complex like an entire city. Sensors that are attached to physical assets can collect and transmit data, allowing the digital twin to be updated with crucial real-time information.
With the advancement of artificial intelligence, machine learning, and the IoT (Internet of Things) for Industry 4.0, digital twin technology has become a staple in modern planning and engineering. Digital twins create opportunities for key personnel to gain valuable inside into performance and risks. The ability to rapidly test multiple scenarios drives innovation and improves performance throughout the product lifecycle.
Applications of digital twin technology
Product design and manufacturing
As technology advances, product developers and manufacturers gain the ability to test drive their concepts and features from ideation through to completion. Digital twins can be used in product design to test prototypes and simulate their lifecycles before any actual manufacturing occurs. 3D models can also be used as mock-ups to gain approval from stakeholders and investors or to assist with user acceptance testing. This prevents the wastage of costs and resources associated with manufacturing, particularly when the product is subject to improvements. Digital twin technology is used extensively in the automotive industry.
Urban and road planning
Digital twin technology can help civil engineers, council officials, and other individuals involved in urban planning and urban design. Spatial digital twin systems allow these people to visualize 3D and 4D spatial data in real-time. This enables them to anticipate patterns and future needs as well as integrate proposed design elements into existing environments. Planners can see how a road or a building will affect the environment, traffic flow, or population, and make calculated decisions that are supported by data.
Understanding structures
The design stage of large physical structures such as offshore drilling platforms involves a large amount of planning and engineering. With digital twin technology, a range of designs, materials, and support structures can be trialed, allowing engineers to make the best decisions while considering various factors such as cost and structural integrity. A digital twin of a structure such as a building can also be useful for interior planning. For instance, it can be used to design ventilation systems or plumbing improvements.
Predictive maintenance
With predictive maintenance, costly unscheduled downtime can be avoided. Digital twin technology allows asset managers to maintain equipment such as large engines or power-generation turbines before a risk or defect becomes severe enough to require a full repair. This saves user asset managers a considerable amount of resources and prevents a whole host of trouble that can result from sudden asset failure.
Reliability engineering
Reliability engineers predict and manage risk and reliability associated with equipment and machine function. The ability to monitor assets and access near real-time data also helps reliability engineers to make more informed decisions instead of having to guessed based on their experience. As digital twin technology becomes more affordable and scalable, reliability engineers can use it to improve the overall performance, efficiency, and resilience of their systems.
Making decisions
Aside from equipment maintenance, digital twin technology can influence a myriad of assessments by allowing decision-makers to find answers rapidly and at a minimal resource cost. Digital twin technology can help building designers measure the structural impact of replacing a material; help traffic planners understand the implications of closing a road; help product designers measure the advantages of adding a new feature. Digital twin technology allows for repeated testing with varying parameters until the most ideal solution is found.
Complex training
Apprenticeships are a traditional way of training specialized workers. But as knowledgeable workers dwindle in number; assets become more complex; components become smaller, the feasibility and efficiency of long apprenticeships and training attachments decrease. Digital twin technology can be used to help tech trainees gain access to a wider range of experience and information, allowing them to learn more in a shorter period and be trained to a more accurate degree.
Reporting and regulatory compliance
As producers and industry stakeholders are increasingly invested in maximizing the utility of resources, the entire lifecycle of a product comes under scrutiny. It is important to not only maintain a view of a product and its components as it is manufactured and used but also after it is retired, decommissioned, repurposed, recycled, or scrapped. Furthermore, many substances such as plastics or heavy metals are subject to strict disposal regulations. Digital twin technology can help ensure that products meet the reporting and regulatory requirements throughout their entire lifecycle.
Digital twin technology is now synonymous with informed planning and decision-making. As smart cities grow, they need virtual models to meet their complex challenges and become more livable and sustainable. In manufacturing and engineering, digital twin technology prevents costly failures and ensures that products perform at their best throughout their entire lifecycle.