Industry 4.0 is the vision for how manufacturers and other companies can use digital technologies to continuously drive greater efficiency, higher profitability, improved flexibility, and better outcomes for customers. One of the leading technologies available to help companies achieve their industry 4.0 ambitions is digital twin technology.
A digital twin establishes a direct connection between a physical asset and its digital representation. But the potential for digital twin technology goes far beyond the convenience of having a virtual asset lookalike on hand. With the idea of a network of digital twins, companies can now increase product insight and work more efficiently across silos in engineering, manufacturing, operations, and service. This enables organizations to bridge the physical and digital world across the entire value chain, helping to drive industry 4.0 excellence.
Insight across the asset lifecycle
The concept of the network of digital twins extends the digital representation of assets to incorporate usage insights made possible from the Internet of Things (IoT). When combined with deep analytics and machine learning, this enables predictive engineering, predictive maintenance, and 3D visualization.
For example, by accessing data transmitted from IoT sensors, you can generate insights at the granular level of the individual machine or component. With this insight, you can uniquely tailor maintenance and repair based on actual usage of the asset rather than on broad assumptions and estimates.
A network of digital twins also connects asset information to business process information, enabling 360-degree visibility that extends across product design, production, maintenance, and service – all while providing insight into business-critical concerns such as costs, supply chain operations, revenue, and customer satisfaction.
This asset lifecycle perspective extends beyond internal operations to vendor relationships, supply, transportation, repair and parts, people and production skills, and business operations. When machine learning is applied to the data across the product lifecycle, deeper insights and rapid changes can be incorporated into a feedback loop that drives better customer service, greater loyalty, repeat business, and ongoing competitive advantage.
The importance of an intelligent core
To realize value from a network of digital twins, companies need a stable, real-time, intelligent core – sometimes known as the “system of record.” This intelligent core should contain and connect to data and applications throughout the enterprise and beyond. It should connect to data regarding financials, customers, assets, and production. It should also connect to your network of digital twins – as this network represents the single version of truth for the assets you’ve deployed.
The intelligent core also needs to access live data from IoT sensors (and, possibly, external data about, say, weather or market conditions). Together with business data from the system of record, you can run analytics to detect challenges ahead of time and act to avoid disruptions in services.
The pluses of in-memory
With digital twin data – as with all data in the digital economy – speed is of the essence. Traditional approaches with relational databases stored on disk are, increasingly, not up to the task. At SAP, we advocate an intelligent core based on an in-memory data storage approach.
With data stored in active memory, speed of access is exponentially increased. This means that you can readily mix historical data from the system of record with live streaming data from IoT sensors – performing analytics and generating insight in real time. The speed of in-memory also facilitates Big Data analytics and machine learning scenarios.
Machine learning enables systems to learn and improve based on information and experience rather than explicit rules or prescribed behaviors, as is required with more rigid historical systems. By analyzing networks of digital twin data from IoT sensors in conjunction with input on business goals, machine learning can help automate processes and suggest decisions that will lead to the best outcomes.
With today’s complex, multi-partner value chains, no single company can expect to deliver all the value for any given product or asset on their own. This is why an intelligent core should also facilitate flexible collaboration with internal business units and external partners. Supported by an intelligent core with in-memory speed, complete data visibility, and cloud-based collaboration, a network of digital twins can help companies succeed in a fast-moving digital economy.
Take, for instance, a third-party logistics provider that delivers warehouse logistics to a consumer products manufacturer. To optimize the movement of goods within the warehouse, the logistics provider deploys mobile robotic units that interact with human pickers to most efficiently route the flow of inventory.
The logistics provider connects machine learning algorithms to the robots through their digital twins, mixing in live and historical business data from the intelligent core, yielding insights at the speed of thought with in-memory data. As the robotic units move goods from picking stations to transport vehicles, the logistics provider aggregates data across all digital twins to get a solid picture of inventory moved. With cloud-enabled collaboration, the 3PL can then share this data with suppliers via business networks to fine-tune supply chain planning.
A network of digital twins can also help out when the logistics provider wants to redesign its robotic units. With this network serving as a single source of truth for the asset being redesigned – supported by an intelligent core that maintains all relevant business data and a cloud-based platform for collaboration – the logistics provider has a solid starting point for a redesign effort that achieves higher levels of performance and optimization.
To learn more about SAP’s digital twin technology, read this IDC Infobrief.