Building a model before we actually develop something large scale is not new to human kind. From miniature building models of yester years, their successors – the 3D CAD models, rapid prototypes or simulations of last decade, to the more recent virtual and augmented reality, the concept of simulation has continuously evolved. Today, digital twins, the dynamic digital representations of any physical entity along with IoT are helping the world realize unprecedented business benefits.
Digital twins were initially used by NASA to visualize, monitor, and modify its spaceships that were so far away. According to Gartner, by 2021, 50% of large industrial companies will deploy digital twins with a 10% gain in effectiveness. IDC predicts the gains from digital twin technology to be as high as 25%. Digital twins find varied applications in equipment performance monitoring and assessment, equipment life assessment, creating a sustainable environment, and in enhancing the digital experience of customers. Here’s how a digital twin can support an enterprise in its transformational journey towards becoming the smart factory of the future.
Digital twins are powered by their ability to integrate data from multiple sources – the Design Data, Operational Data, and the Maintenance Data. These data define the actual asset or a process, with which intelligent models are built. When such a data-rich model encounters deep product knowledge, physics, and powerful industrial analytics, an active digital twin is born. Enterprises that have prioritized their use cases in-line with their operational and business strategy can tap various benefits of digital twin technology.
Innovative Business Models
Digital twins can offer new services and create exponential value for businesses in more ways than one:
Product as a Service model: Enterprises are taking the servitization route to provide value added services to their customers. In the process, they are creating ancillary revenue opportunities for themselves. This servitization model also reduces service chain leakage to third party service providers.
Product differentiator model: OEMs sell analytics insights and predictive/performance services derived out of the digital twins of their products as differentiators to their products. This helps them gain more market share and customer delight.
Asset additional value generational model: Digital twins can bring in huge savings and efficiency gains to an enterprise when deployed for predictive/prescriptive maintenance and operations optimization. For example, a coal powered boiler that requires a combustion tuning period of 14 days can be optimized to 12 days using a digital twin. This saves about three million USD per boiler tuning.
It’s not just products or physical assets that can be twinned in the digital world. With the possibilities of aggregation, various internal processes can be virtually established and evaluated. This opens the doors for process industries to arrive at vital decisions by simultaneously working in the virtual and physical world. Microsoft foresees that by leveraging the power of mixed reality and insights from a process digital twin, such industries can achieve cost effective process designs and virtually commission them with a 20% productivity improvement in the upcoming decade.
Enterprises would do good to assess revenue, profits, return on investment (ROI), and cost optimization against the perceived value and benefits that can be derived out of a digital twin.
Today’s customers not only expect great experiences, but they want these experiences to be fine-tuned to their very special individualistic needs and wants. The data collected through sensors and fed into the digital twins of products can provide valuable insights on each customer’s unique requirements regarding the usage of the product. The same concept can be applied to every working equipment in the factory or even their processes to customize them and make them more efficient than ever before. The OEMs / product manufacturers can then feed these inputs back into the design or the R&D phase to deliver an asset / product that exactly meets the various needs of a particular customer.
In field services at customer sites, your service engineers can receive analytics output from a digital twin on their digital wearable or handset as a notification or alert. They can carry out optimal or remedial actions immediately. Imagine the extent of customer gratification when as an OEM you can promise them minimal asset / equipment down time with such on the spot remedial actions.
Digital Portfolio Risk Management
With digital twin your insurer can get data and therefore greater insights into the likely performance, lifetime, and behavior of your asset. These asset insights can be translated to identify, manage, and mitigate risk, thereby considerably avoiding down time and loss of productivity.
Performance monitoring and life assessment will also enable insurers to model likely scenarios and plan their risk portfolio to maintain an optimal balance of risk.
Digital transformation in the Industry 4.0 era is all about realizing leadership across digital ecosystems. Digital twin enabled smart factories of the future need to harness the abundance of data and insights to take advantage of the digital ecosystem. A right partner with domain mastery across various industries, vast data science expertise, and rich digital twin experience can help you keep ahead of the race of digital transformation.
About the author(s)
Rajaravisankar Shanmugam (Raja Shan), is the Global Head - Business Development for the Internet of Things (IoT) Business at TCS. He is responsible for developing the IoT Business, thus leading the global IoT Sales, Marketing & Analyst Relations, and developing strategic Alliances & partnerships. He is a leading voice in Internet of things space, delivering the keynote address at prominent industry events and has published various works of thought leadership including an article on realizing business value from Internet of things.