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Digital Twin: The future beckons


| January 12, 2018, 3:52 PM IST

At a wind farm on a remote hilly terrain in an Indian state, there seems to something seriously amiss. Of late, the output from the farm has been dipping, and not aligned with the predictions. The dip in generation indicates that a wind turbine or possibly even more at the farm are not performing optimally.

With the limited inputs at power producer's disposal and the physical distance, it would be almost impossible to diagnose, let alone resolve the issue from afar. But if there is a digital model of the wind turbines that mimics the actual turbines remotely, we could potentially solve this problem. Called Digital Twins, these are digital representations of the physical assets. With the aid of sensors placed strategically, Digital Twins not only replicate real-time performance but also helps to diagnose problems before they could potentially occur, and resolve them remotely.

The digital wind farm is just one instance of how Digital Twin can help drive outcomes for wind farm owners, through remote management. There are numerous applications of this technology across the industrial landscape, from aviation to healthcare. And the best part is that the market is just beginning to grow.

According to research analysts MarketsandMarkets, the digital twin market could easily touch $15.66 billion by 2023 (consider it was just $1.82 billion in 2016) at an impressive growth rate of 37.87% CAGR during 2017-2023.

The excitement is fairly understandable. Digital twins can help immensely in equipping teams into conceptualization, comparison, and collaboration for high-end innovations and problem-solving with the same strengths and agility as it empowers those entrusted with fixing on-ground/air issues that assets suffer during their active lives. With some great underlying capabilities, this technology furnishes real-time status and working conditions of the physical objects through the mechanism of data pulled in from the sensors installed in the physical objects.


Take the case of the wind power industry. Three years ago, the Government of India passed a regulation (Renewable Regulatory Fund) to accurately forecast power generation from a wind farm. However, this is not very easy to do because determining wind speed is difficult. There were a lot of companies providing services for wind and weather prediction, but not with good accuracy (between 80-85%). GE’s technology team demonstrated that their self-learning algorithms, when applied to real wind farms, produced results that were 5-7% better than the best solution available in the market; and a better prediction with 94-95% accuracy. This resulted in immense saving for the wind power producing companies.

Digital Twins can also play a big role in the aviation sector. For instance, GE noticed that jet engines as they start flying in different environments – where some are hot and dusty while some are cold; generic models and averages would not work for all. The usage recommendations will not be accurate. So, GE started building Digital Twin of different components of the engine. Using models according to where, and in which environment an aircraft will fly, and the weather conditions they operate in, GE then recommends prescriptive maintenance for the customer, thereby saving millions

Locomotives are also being powered by Digital Twins. For instance, one of GE’s popular locomotive Evolution uses Trip Optimizer, a feature that continually gathers and analyzes specific insights in real-time. The data is used to calculate the most optimal way for the locomotive operator to drive the train and achieve maximum fuel efficiency and lower emissions. Operating with Trip Optimizer software, can helps rail companies save 8-10% on fuel, or 32K gallons saved/locomotive and 174k tons of emissions decreased per year.

Like mentioned earlier, Digital Twins application is being seen across the asset lifecycle. So if they are helping maintenance teams resolve problems before they pop, they are also augmenting customer experience by letting the design guys get a better grip on customer needs, and drive apt enhancements to existing products, operations, and services, while also helping create clever and precise innovation for new offerings.

The best part about the Twin is the technology that powers it. Built on Cloud Foundry open source technology, Predix provides a standard way to connect machines, data, and people. The platform also boasts of a vibrant ecosystem that has many developers creating specific apps for it. But unlike the mobile apps, these are much complex and detailed.

One of the best instances of application of the Digital Twin on the Predix platform is the digital wind farm. Overall, digitization helps in as much as 20% gains in terms of efficiency. The idea is to work smartly by analyzing the data from each turbine that is fed to its virtual equivalent.

Not surprisingly, when it comes to smarter maintenance, these twins can empower technicians with historical and real-time data and then bolster it with predictive algorithms for sharper insights into potential failures much before they occur. This way the operations-people can indulge in the unprecedented convenience of remote preventative adjustments.

There’s more. In case, a site visit is inevitable, a technician can still tap the dashboard and remotely diagnose the root cause of the problem. This helps to order the necessary parts before visiting the site to perform the repair.

Apart from the maintenance bit, there is also the case of creating innovative solutions. Imagine, a design team that is armed with nuances and mysteries of real-world usage of existing products? With never-before insights brought by Digital Twins on how products are being used by customers and where they lack or need more thinking; new product design can work wonders with market penetration and customer satisfaction. That’s the power of Digital Twin.

In the end, the march of digitization is inevitable. Research firm Gartner Inc. has named the Digital Twin one of its top 10 strategic technology trends for 2017 and expects the next three to five years to show billions of things being represented by Digital Twins. Already, GE Aviation happens to monitor as many as some 35,000 engines worldwide and these run on a variety of planes in many airlines across the globe. Digital Twins are now mimicking locomotives, MRI scanners, and so on. There is hardly any industrial sector that cannot benefit from an application of the same. There are quite a few turbines on Indian hinterland which have a digital counterpart in some urban center. As time passes, the digital movement will pick up pace, and there will be a lot many Digital Twins that will make our lives easy and efficient.


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