First applications of the digital twin: Lenze at Hannover Messe Digital
12 April 2021
The perspective is clear: every factory, every machine, every component gets a digital twin and customers can then go through it, asset by asset – all the way to the sensor, the entire life cycle from engineering at the machine manufacturer to maintenance at the operator and beyond. In the future, the digital twin will be as self-evident as the provision of data sheets on the website today.
This is why Lenze has been researching the digital twin for several years and is now taking further steps into application. Developers and designers can create the first digital image of a machine via a web service, the EASY System Designer. Further web services then enrich this structure directly with technical data and documentation of the equipment used. The resulting digital twin creates a new standardised and automated consistency of data and information and is the basis for use in further tools and applications. And these are only the first steps.
"We are moving into the concrete implementation, we will provide asset data of our system components, such as the digital type plate, technical data and documentation, via web services. This may not sound very exciting at first, but the added value over the entire life cycle of a system is enormous – because this data is passed on from engineering to commissioning to maintenance," explains Patrick Bruder, Business Development Manager Automation at Lenze.
Common data base
The provision of component data by the supplier simplifies integration processes in the development project. The goal is to bring products to market faster and more cost-effectively by avoiding duplicate modelling work and, ideally, completely hardware-free development.
The automation specialists from Hamelin want to move away from the pure visualisation of a product. A digital twin is the complete digital representation of a machine or system in all its aspects. It is not necessarily a specific file or model, but rather a bracket around all versioned and referenced data of a product. In this way, all tools can work on a common data master over the product life cycle, which is successively supplemented with further information.
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