Three advances in AI and ML: From Awareness to Action and Decision

Digital twin to couple production and adoption

Prevalent in manufacturing already, this second AI advancement will take industries by storm. Simply put, “digital twin” is a connection between the physical and virtual worlds. Digital twin integrates big data, AI, machine learning (ML) and IoT with data to create living digital simulation models that update and change as their physical counterpart changes. Like an avatar of the actual product, digital twin allows the creator to visualize the status and condition of a product that may be thousands of miles away. It can provide new insights into how products can be better designed, manufactured, operated and serviced.

According to a 2017 IDC report on “Worldwide IoT 2018 Predictions,” by 2020, 30 percent of G2000 companies will be using data from digital twins of IoT-connected products and assets to improve product innovation success rates and organizational productivity, achieving gains of up to 25 percent.

As a technology, digital twins allow for improved prediction, greater visibility into the operations of machines, perform root cause analysis and/or what-if analysis. This simulated virtual system will redefine the way services, products and processes are executed. 

Let’s take the same scenario cited above—post-product launch. Assume this product is a self-driving car. For the manufacturer, a digital twin allows for visibility into vehicle performance, wear and tear of components, servicing schedules, etc. This in-depth visibility allows manufacturers to predict and prescribe fixes on the virtual system, test them and then implement the patch on the actual system.