Cloud Computing 101: Digital Twins

January 31, 2019

Digital Twins is a concept that has been around for decades, but has recently become a hot topic in the technology world. It is most popular in the Healthcare, Automotive and Manufacturing industry and the growth of IoT is one of the reasons that the digital twin concept is becoming a reality for some many businesses. A digital twin is a virtual representation of a physical object or system – but it is much more than a high-tech lookalike. Digital twins use data, machine learning, and the Internet of Things (IoT) to help companies optimize, innovate, and deliver new services.

 

At its simplest, a digital twin is a virtual replica of a physical product, process, or system. Digital twins act as a bridge between physical and digital worlds by using sensors to collect real-time data about a physical item. This data is then used to create a digital duplicate of the item, allowing it to be understood, analyzed, manipulated, or optimized. Other terms used to describe digital twin technology over the years have included virtual prototyping, hybrid twin technology, virtual twin, and digital asset management.

 

SAP and Digital Twins

 

The network of digital twins institutes a real-time single source of truth – everywhere. It creates real-time, secure communications and a collaborative environment within the business while encompassing relevant external networks. The network includes not only the digital representation of the physical product or asset, but also the commercialization aspects represented by the ERP business system of record. 

 

According to SAP, Digital Twins must have the following characteristics:

 

  • Identity – a digital twin represents a single, unique physical asset; though we would prefer a 1-to-1 cardinality between asset and twin, business outcome considerations may imply a 1-to-N cardinality, each describing a different dimension; the digital twin can be instantiated at the creation (e.g. engineering, production, configuration, installation) and lasts until the asset is retired (or beyond if historic data is required)

  • Representation – capturing the essential physical manifestation of the real asset in a digital format, typically using formats such as CAD, MES, or engineering models with corresponding metadata and classifications; traceability between digital twin and physical object is ensured through serialization

  • State and events – reflecting real asset state (e.g. condition, location, speed, environment) in (near) real time providing information on properties that describe various aspects that the digital twin is built for; the digital twin triggers alerts and events on behalf of the object; historic state is typically recorded

  • Context – describing operating context such as physical installation, ownership, reference to financial or asset management information, roles and business partner involved, service level agreements, service work performed on the asset

  • Interaction – all properties above must be securely and digitally queried in a software system by other systems (via APIs) or users 

 

Because it manages and controls extensive variability in product and asset configurations, the digital twin of one becomes the true single source of truth. It bonds the  unique digital design of every product or asset to its  physical representation throughout the lifecycle. Companies can then address product individualization; accelerate time to market; provide a mechanism for the delivery of new business models; and ensure effective, timely performance of asset maintenance and repair. Furthermore, the network of digital twins that monitors distributed assets enables collaboration with partners  when managing assets as a service or engages suppliers  when defining part and assembly requirements and enhancing change management.

 

The approach combines digital twins with manufacturing solutions from SAP, cloud networks  and SAP Leonardo capabilities, including machine learning, blockchain and Internet of Things (IoT), to optimize the product lifecycle with:

 

  • Digital representation: SAP synchronizes digital twin business data, product information, asset master data  and IoT-connected data from both on-premise and cloud solutions enabling companies to represent the world digitally. Solutions including SAP Predictive Engineering Insights, SAP Predictive Maintenance and Service and the SAP 3D Visual Enterprise applications provide access to  rich data processing capabilities and live configuration, state, condition and control information.

  • Business process: Rich enterprise-grade data processing capabilities allow customers to create, access and update digital twins to support business processes. SAP solutions provide an integrated data model from design, production and maintenance to service, including packaged integration to existing systems for computer-aided design, ERP, and product lifecycle management. Offerings providing end-to-end process support for manufacturers and operators include SAP S/4HANA, the SAP Engineering Control Center integration tool, SAP Hybris Service Cloud solutions, and  the SAP Manufacturing Integration and Intelligence and  SAP Manufacturing Execution applications.

  • Business networks: With leading network offerings such as SAP Ariba solutions, SAP Asset Intelligence Network, and the SAP Distributed Manufacturing application, SAP is uniquely positioned to provide a virtual platform for collaboration on products and assets. The network of digital twins enables secure data access, sharing and governance on a global scale.

  • Networks of digital representation: SAP enables  twin-to-twin connections in systems within a specific  asset and on an asset-to-asset level. SAP solutions such  as SAP Asset Intelligence Network provide semantic and industry-standards support in an asset core modeling environment to enable live enrichment during the product or asset lifecycle.

 

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