Model based approaches to Digital Twin
A Digital Twin may be defined as an operational virtual model of a physical component or machine. As such, the idea of Digital Twin has been around for several years, especially in the Aerospace and Automotive sectors. What truly differentiates a Digital Twin from a simulation model is the area of application, that is shifted towards operations and servitization, and the integration with IIoT technologies or automation design tools. Referring to a simulation based model of a production machine, for example, the requirements may include the ability to detect issues with the real machine counterpart throughout its operating life, or the ability to enable strategies for compensating decreased performances without slowing a production line. Other than predictive maintenance, digital twin enabled servitization may entail optimization or zero defect manufacturing strategies based on process or machine models.
To exemplify these scenarios, two different approaches to Digital Twin development will be presented. A model based approach for the development of Digital Twin of production machines will be described, whereas a model of the machine is created and afterwards integrated with automation design software using the FMI technology in order to provide virtual commissioning capabilities. A second example will be presented whereas a process simulation model is used to create a surrogate process model (meta-model), that is afterwards used in combination with data recovered by sensors and HMIs in order to provide production quality prediction and control capabilities. In this latter example implications regarding the management of data will also be presented.
Giovanni Borzi, M.Eng., joined EnginSoft in 1997 and is Partner of the firm. Since 2011 he is managing the Applied and Industrial Mathematics technical area. In 2010 he completed a one year master course “Project management and innovation management” at the University of Padua. In 2011 he earned the PMP – Project Management Professional certification from the Project Management Institute (USA). Mr. Borzi has a relevant experience as Project manager, and as WP and Task leader for EC projects co-funded under the FP7 and H2020 Programmes, with a focus on advanced manufacturing research. As a simulation expert, he has been recipient of an Experienced Researcher grant under the EC Marie Curie People programme, Industry-Academia Partnerships and Pathways. He served as council member of SIMAI, the Italian association for applied and industrial mathematics from 2013 to 2016.