Increased efficiency in virtual commissioning with automated model generation based on component libraries

Abstract

The use of Virtual Commissioning (VC) is becoming increasingly relevant for the engineering of automation systems. VC allows for validating concepts and design solutions in the early phases of product development, thereby improving communication among disciplines, reducing the costs for bug fixing and accelerating the overall engineering process, in particular the commissioning of plants and machines. However, as an additional software tool in engineering, the introduction of VC causes initial training and more importantly continuous extra modelling efforts. An approach to overcome this flaw is the automated generation of VC models based on existing engineering information from the system or domain level - ideally in tandem with the reuse of solution models from previous project. The latter can prove particularly beneficial in the context of modular building-block systems as often pursued in automation engineering.This paper presents a practical implementation of an automated VC model generation solution based on system structure and layout models combined with an object library containing additional model information of the applied automation components. The presented use case addresses VC simulation models of intralogistics warehousing systems where the layout plans provide information about type, position and dimension of predefined subsystems, modules or components which are then being analyzed and merged with additional model information. By means of a specific exporter the assembled model information is being filtered and transferred into the simulation environment via a standard API. Significant time savings could be demonstrated in this use case. Based on these results a generalized framework for more efficient interdisciplinary engineering processes based on automated data exchange as well as automated model transformation and generation has been derived and will be presented along with an outlook on future research activities.