Simulation-based Digital Twins -

Simulation-based Digital Twins

Digitally packaged, visualized value chains support management with forward-looking planning.

The first digital twin solution emerged in 1960 as a replica of the Apollo 13 and helped prevent further catastrophes of the space adventure. PALFINGER, a company that manufactures cranes, is one of the first movers to have invested in the Digital Twin as a software concept for construction services. The company is also in the spotlight in space projects such as China’s most ambitious and challenging lunar adventure to date. With precise processes and excellent stability, the PALFINGER PK 19000 loading crane ensured that China’s space probe was successfully recovered at extreme temperatures of less than -30 degrees Celsius.

StrucInspect, the joint venture between PALFINGER, the engineering specialist VCE and the mobile mapping and photogrammetry experts of the ANGST Group, uses DataArt to develop digital twins as software-as-a-service for construction, industry 4.0 and mobility.

In 2002, Dr. Michael Grieves introduced the concept of the digital twin as a digital representation of a physical object or system by integrating real-time data with its digital representation to gain insights into the asset and estimate its lifecycle. From oil rigs to bridges, factories, production lines, buildings, cars, devices, processes, or human organs, use cases for digital twins have been found in aerospace, energy, construction, automotive, medicine, urban planning, and more identified.

Digital twins are designed to support the performance and continuous improvement of linked assets and processes. As a digital twin combines different data, intra-asset effects and dependencies become transparent. Decision points can be codified and automated based on insights from a digital twin, reducing the number of iterations between decision makers.

Digital twins will also bring together planning, design, construction and operational data across industries. A common data model or set of models simplifying the process of connecting applications in a specific domain is intended to accelerate this development – ​​twin builders of cloud solution providers point to this future.

Digital Twins = more agile, leaner, more environmentally friendly

DataArt, global software engineering for customer-specific requirements, supports companies with its centers for digital excellence in building AI-driven digital twins of their assets. Digital twins make companies more agile, their operations leaner and more environmentally friendly, since data is increasingly integrated into applications and systems through its modern use.

Because digital twins are responsive and constantly evolving as more data is fed to them, such as data from artificial intelligence (AI), sensors, or the Internet of Things, they can predict events and recommend or execute decisions based on real-world conditions or simulations . Engineers use operational data for comprehensive twins by considering what-if scenarios for behavioral simulations. In the future, we will contribute more and more to creating autonomous twins that are able to learn and act. DataArt supports all 5 phases of a digital twin journey with the aim to increase interoperability between applications, platforms and sensors and to develop custom or adaptable models that accelerate the testing of new use cases for industrial capabilities or assets.

A digital twin is a single source of operational information for an owner/operator, reducing total cost of ownership, achieving higher operational efficiencies and unlocking previously untapped value. With multidisciplinary models at the core of a digital twin, DataArt can help integrate systems and data across workflows and between organizations.

Deploying digital twins across ecosystems and supply chains requires full digitization of value chains. This enables an overall view for decision-making from design to aftersales, optimized automation of processes or a combination of discrete and continuous production through AI-controlled processes and the control of machines. Multiple digital twins can be integrated into entire ecosystems, spanning regions and balancing supply capacities according to dynamic demand requirements.


1) Digital twins help transform the construction industry, George Lawton, VB, The Machine, Making sense of AI, June 18, 2021, the-construction-industry/

2) Palfinger in the spotlight at China’s moon mission, Palfinger, December 2020,

3) Technology deep dive: digital twins, expert interviews; Gartner IoT implementation survey (2018); IDC FutureScape: Worldwide IoT 2018 predictions, IDC, October 2017; Fraunhofer institutes; McKinsey analysis, McKinsey & Company, %20slides%208%209%2010

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