How Digital Twins are driving the future of business
C V Ramachandran, digital transformation and operations improvement expert at PA Consulting, discusses use cases for digital twin technology.
The article notes that digital twins are a virtual representation of a physical object. It could be anything – as complex as a car or a manufacturing production line, or as simple as a piece of furniture. The digital twin emulates all the parts of the object (or set of connected objects) to create a virtual proxy. A car’s digital twin would model its shape, tires, seats, engine, transmission, everything. Companies use a digital twin to design a 3D model of the original, enabling teams to analyze the performance of the object under different conditions. Successfully deployed, digital twins can save serious money, improve product designs, and elevate efficiency and productivity.
Up until now, heavy industries that work with large assets and have adopted product lifecycle management systems – those including oil and gas extraction, aerospace, and automotive – have been leaders in digital twin adoption. But that has been changing in recent years because the components that make digital twins possible and useful are now much less expensive, easier to use, and easier to access.
Over the long run, digital twins will form their own networks, which experts call a “digital thread.” If a digital twin enables us to create a digital representation of a piece of equipment or facility, then a digital thread is the continuous, connected stream of information provided by an intelligent asset throughout its life cycle, from design to decommission.
Digital twins are a virtual representation of a physical object. It could be anything – as complex as a car, or as simple as a piece of furniture.
Implemented effectively, digital twins can serve as strategic catalysts. They can provide visibility into an organization’s processes and ways to improve them and, in turn, strengthen customer relationships. Digital twins provide a sandbox where innovations can be tested and refined before they’re launched into the real world. They afford businesses a cost- and time-efficient way to design smarter products and assets while capturing more information about them. So too, they enable companies to make products better, faster, and safer and generate new revenue opportunities. These include service offerings that create as-a-service business models, which remove the burden of large capital outlays and lifetime maintenance from the customer and keep them connected with the service provider.
To create a digital twin, you need to record the base information about the object and capture how it’s performing and being used.
As the cost and complexity of digital twins has fallen, their adoption has spread beyond manufacturing to many different types of businesses.
CV says: “The cost of sensors continues to decline, the amount of data collected is exponentially growing, and storing is affordable in various cloud services. Manufacturing companies can tap increasing opportunities to gain insights. The interest is in getting all this data off the factory floor and analyzed to help understand not only what’s going on today, but also forecast what plant operators can do in the future to improve productivity and quality.”
Future possibilities for digital twins
In addition to researchers looking at operators on the factory floor, experts point to other possibilities for digital twins:
- Logistics: Digitally enabling supply chains holds potential for creating more efficient, resilient, and sustainable global trade. By twinning products in transit and the transit itself, real-time visibility into where a shipment is would enable better decision-making if, for example, an enormous ship got stuck in the bank of the Suez Canal. (Not that that would ever happen, of course.)
A digital twin could identify and solve many “what-if” scenarios to enable better decision-making for highly complex supply chains. This vision of creating digital twins of supply chains has a major obstacle to overcome: sharing intelligence. Companies often hold their data close and that gets in the way of efficiency. CV continues: “The best solution we have found is to simulate the supply chain really well to the warehouse level and then, depending on how close we are with our supplier, we can make them part of a digital twin.”
- Sustainability: Using digital twins to improve sustainability index scores is also on many businesses’ radar, according to Ramachandran. In this application, digital twins work by suggesting the most environmentally sustainable method or path – like how a product is shipped or the raw materials are used in production.
- Pharmaceuticals: Digital twins, along with artificial intelligence (AI) and machine learning, can accelerate drug discovery and testing by first modeling them before going to clinical trials.