digital twin

Data is indeed at the core of digital twin technology: Oracle

Application of Digital Twins is versatile and can work for various industry sectors including automotive, food and beverages, pharmaceuticals, power utilities, transportation & logistics, aerospace & defence, and data centres, to name a few.

With the Internet of Things (IoT) becoming prolific with industries like agriculture, applying sensors to machines such as a tractor, is helping to monitor and predict failures before they happen. As the model is in the cloud, monitoring a tractor and its surrounding environment such as the weather can be done remotely.

Pradeep Agarwal, Senior Director, ERP Cloud, Oracle, talks in detail about how SaaS ingest data from a multitude of sources and display results on dashboards and can even trigger actions to be taken, either manually or automated and how with sensors and digital twins, it’s easier to gain the visibility and insights to identify any problems before they occur.

 DQ: What is the role of digital twin in the Indian IT landscape?

Pradeep: India is a burgeoning economy, for which the next decade of manufacturing will focus on adopting cognitive solutions that infuse intelligence into all processes – from a factory’s floor to the finished product.

Digitalisation of the industries can optimise them, but deployment of digital twins has the potential to improve scalability, reduce the cost of production, minimise production defects, and reduce production time.

In process-driven functions, digital twins constantly receive data feeds from interconnected machines, helping in predictive maintenance and running the business as usual without downtime. Many key industry verticals in India will benefit from this.

DQ: What challenges foes the industry face in linking technologies like IoT, AI, ML with digital twin?
Pradeep: One, there is a clear gap between technical skills and digital dexterity. Two, there are concerns around data
security. Three, handling data growth is something organizations often grapple with.

As more companies become dependent on AI usage, they will be faced with more data that is being generated at a faster pace and presented in multiple formats.

To wade through these vast amounts of data, AI algorithms need to be able to combine data that might be of different types and time-frames. Deployment of digital twins can be revolutionary in tacking these issues.

Predictive maintenance solutions powered by digital twins help in precisely monitoring, and timely recognizing potential anomalies within a system.

For instance, a predictive twin offered under Oracle IoT Intelligent Applications can detect future problems or state of a machine and can determine trends and patterns from contextual machine data. With this information, problems
like potential security can be addressed in advance to prevent loss of time.

DQ: In which sectors can businesses refine their operations by implementing digital twin technology?

Pradeep: Application of Digital Twins is versatile and can work for various industry sectors including automotive, food and beverages, pharmaceuticals, power utilities, transportation & logistics, aerospace & defence, and data centres, to name a few.

Let’s take agriculture for example. Before we had digital twins, a mechanic had to be physically present in the field to monitor the oil level, filters, coolants and more. However, with digital twin technology, a digital replica of the tractor can be designed to show what the tractor looks like from the outside, and inside. And, with Internet of Things (IoT) becoming creative with industries like agriculture, applying sensors to machines like a tractor, is helping to monitor and predict failures before they happen and remotely predict surrounding environment such as the weather.

Similarly, manufacturing is the area where rollouts of digital twins are helping factories simulate their processes. The technology is playing an instrumental role in healthcare.

A striking example of this is the release of ‘Living Heart’ by Dassault’. It is the first realistic virtual model of a human organ accounting for blood flow, mechanics and electricity. The software can turn a 2D scan of a human into an accurate full dimensional model of an individual’s heart. Such usage can help doctors discover undeveloped illnesses, experiment with treatments, and improve preparation for surgeries.

DQ: How is Data core to Digital Twin technology and how does it help in delivering value and unlock data insights?

Pradeep: Data is indeed core to the digital twin technology. Two-way communication between the physical and digital is essential for digital twins. Data flows from the physical asset to the digital twin and vice versa. That data is leveraged using data science—whether that’s artificial intelligence, machine learning, or basic data analysis. Insights derived from this data helps provide better decision making resulting in interventions that are fed back to the physical asset, providing better outcomes. The more that machine-to-machine data exchanges are used, the better the results are.

Digital Twin is delivering value by unlocking data insights in ambitious ways. For example, Singapore has created a complete digital twin of the city-nation to track traffic, pollution, climate, and city layouts so city managers can test accessibility options, see the potential impact of new construction, manage emergency responses, and monitor city health. Meanwhile, doctors are creating patient-specific Digital Twins of lungs to help make decisions about ventilator use when treating COVID-19 patients.

DQ: How digital twin is vital to the expansion of IoT technology?

Pradeep: A Digital Twin is essentially a virtual model of a physical device. They are used by IoT developers, for running simulations without an actual physical device. In one way or another, digital twins can be credited for the burgeoning growth of IoT.

An IoT device takes its place like a physical object in the concrete world. A digital twin on the other hand is the virtual representation of the same IoT device which exists within a system. It basically replicates the physical dimensions, capabilities, and functionalities of the IoT device in a virtual environment. Hence, the intrinsic connection between the two.

For instance, IoT in healthcare takes the form of patient wearables, fitness trackers, medical devices etc. Digital twins on the other hand enable creators to test and pilot newer functionalities, enable the device to take precise readings, and come up with inventive ways to swap data with the servers. Doctors can use the digital twins of patients to monitor their vitals real-time. There are numerous examples like these which substantiates the point that penetration of more digital twins across industries is bound to expand the use of IoT.

 DQ: What kind of solutions Oracle is offering around this new technology? And how are you helping companies in transforming their businesses?

Pradeep: Oracle IoT Intelligent Applications core offering includes key digital twin elements including virtual twin, predictive twin and twin projections. In a virtual twin, Oracle’s device virtualization feature creates a virtual representation of a physical device or an asset in the cloud to retrieve a last known status or to control operation states of an asset. In a predictive twin, the digital twin implementation builds an analytical or statistical model for prediction by using a machine-learning technique.

This model can detect future problems or state of a machine and can determine trends and patterns from contextual machine data. With this information, problems can be addressed in advance to prevent downtime. Twin projections take predictions and insights and integrate these with back-end business applications. These projections can trigger workflows.

Transactional and contextual IoT data insights can be used for faster better decision-making and for monitoring the predicted state of machines and their environments. Oracle Engineered Systems that use cloud equivalents like Oracle Exadata Cloud Service can also help bring down the cost of a digital twin strategy. Big data infrastructure like Oracle Big Data Appliance is helpful in wading through copious amounts of data. 

DQ: What is the future of Digital Twin in India in the coming years?

Pradeep: The Indian IT industry has grown exponentially with its contribution to India’s GDP going from 1.2% in 1998 to 7.7% in 2017. Technology trends like mobility, cloud computing, analytics, AI, SaaS, IoT are fast changing the dynamics of the market. The Indian IT industry continues to adapt to the changes in the technology space very promptly.

Furthermore, with the government’s progressive policies on digitization which has enabled cloud and AI based initiatives like digi-lockers, E-hospitals, E-pathshaalas and BHIM app to name a few, use of digital tools is likely to go up. Also, with manufacturing sector and SMEs expected to grow exponentially in the time to come, harnessing the capabilities of digital twins can help them upgrade and adopt new designs and components much faster to stay aligned with the needs of the industry.

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