The Internet of Things and digital twins are changing the ways digital and physical interact. IoT provides the connection and access to intelligence in the physical world and interlinked with digital twins, which are digital models that virtually represent their physical counterparts.

In 2020, IoT must be a key strategic consideration in order to realize the full potential of digital twins of physical products, operational processes, or person’s tasks. The physical world experiences of these three ‘P’s’ – products, processes, and people – captured through sensors and IoT is a fundamental requirement of a true digital twin.

Digital twins fulfill their terms by being live and dynamic whereas lesser terms, including digital replicas and shadows, imply minimal real-world implications and less impactful use cases. ‘Twin implies that what happens to one happens to the other, in a mutable fashion’, which puts IIoT as the bi-directional link to enact this and empowers the transformative use cases that come with it.

Ways in which IoT Is Enhancing Digital Twins :

1. IoT Offers Visibility Into the Full Product Lifecycle

Smart connected products are replacing assumptions with facts; real-world IIoT data closes the feedback loop with product usage data, which then informs future iterations – and even business model changes, including product-as-service. Product telemetry also gives engineers and product designers behavioral characteristics of deployed products or fleets of products.

Providing a frame of reference to compare the ‘as-is’ versus ‘as-used’ product usage is an extremely powerful IIoT-enabled insight that can inform the development of future product iterations. Its applicability can range from replacing or modifying certain features to drilled-down insights into the specific performance of part(s).

Expanding visibility into the product lens through cross-functional collaboration can also drive downstream efficiencies. This includes change management in manufacturing and service processes, which lowers scrap, rework, and lead times.

Real-World Example: Whirlpool is achieving data-driven design by connecting deployed appliances through IIoT and analyzing operating performance metrics (torque, drum speed, motor temperature, etc.) across fleets of products to improve future iterations.

2. Digital Twin of Processes: IoT Unlocks Deeper Operational Intelligence

Much of a product’s operational condition and performance in the end user’s environment hasn’t been accessible to the manufacturer or customer. With maintenance and service being critical functions to reduce asset downtime and differentiate offerings, digital twins with IoT can drastically improve these metrics and enable new revenue streams.

Digital twins can bolster remote service where software updates, patches or reboots for deployed assets can negate the need to send a technician on-site. IIoT’s flexibility can enable mission-critical systems to sample data every second to inform services, or less frequently to optimize resources, all depending on the digital twin use case.

Telemetry data can also feed into the deployed asset’s digital twin to gain a baseline of its health and apply next-generation predictive maintenance modules blending machine learning and physics-based simulation techniques. Simulating historical patterns of machine performance with design expectations against real-time sensor data will reduce unplanned downtime and add another layer of intelligence, which further maximizes asset utilization.

Bringing the Digital Twin to Life

The full fidelity of a digital twin will become available as IoT is added to organization’s products, processes, and people. This ‘live’ data will also serve as an entryway for next-generation use cases, as it’s a lucrative inputs for physics-based simulation, artificial intelligence, and computer vision applications. Therefore its right time to start on a digital twin strategy.

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