Volume 64, Issue 3 - Special Issue: Cross-discipline Modeling and its Contribution to Automation / Birgit Vogel-Heuser, Stefan Biffl

The article demonstrates the advantages of meta-model-based solutions for multi-aspect automation tasks. Multi-aspect tasks require solutions that consider information of multiple system aspects simultaneously. In today's practice, these aspects are maintained in different tools which make implicitly use of tool-driven system models. In contrast, we propose to prioritize the models in order to facilitate the handling of multi-aspect automation tasks. The article exemplifies this idea by introducing typical automation and engineering models and illustrates their utility in a use-case example.

Zusammenfassung Im Planungsprozess automatisierter Anlagen wächst die Menge vorhandener Informationen über die Anlage und ihr Automatisierungssystem. Verschiedene Gewerke, Abteilungen und Spezialisten wirken an der Erstellung und Bearbeitung mit und fügen ihre Arbeitsergebnisse den bereits vorhandenen Informationen hinzu. Der vorliegende Beitrag zeigt, wie durch den Einsatz wissensbasierter Methoden diese Anreicherung von Informationen während der Planung automatisierter Anlagen unterstützt werden kann. Hierbei werden sowohl die Strukturen von AutomationML als auch zusätzliches Wissen in Form von semantischen Netzen, repräsentiert in OWL, angewandt und miteinander verbunden. Das universelle Konzept wird exemplarisch anhand der Security-Analyse einer automatisierten Anlage erläutert und validiert.

Zusammenfassung Inkonsistenzen, die im Engineering mechatronischer Systeme auftreten, können teuer werden – vor allem, wenn sie zu spät erkannt werden. Die Herausforderung, Inkonsistenzen in den verschiedenen Modellen mechatronischer Systeme zu spezifizieren und zu diagnostizieren liegt dabei vor allem in der Verschiedenartigkeit der Disziplinen. Folglich untersucht dieser Beitrag aus wissenschaftlicher Sicht die Anforderungen an die Spezifikation und Diagnose von Inkonsistenzen und schlägt ein Konzept für ein wissensbasiertes Framework vor. Hierzu werden Semantic Web Technologien eingesetzt, da diese sich aufgrund ihrer Flexibilität und Erweiterbarkeit für den Einsatz in heterogenen Modellen besonders eignen. Anhand eines Anwendungsbeispiels werden die Erkenntnisse für Praktiker illustriert und die Stärken und Limitationen eines solchen Ansatzes diskutiert.

Industrial cyber-physical systems require complex software to orchestrate heterogeneous mechatronic components and control physical processes. This software is typically developed and refined iteratively in a model-driven fashion. Testing such multi-dimensional systems is extremely difficult as subsequent refinements may not correspond accurately with previous system models. We propose a framework to generate test-cases from functional requirements at all stages in the model-driven engineering process. A requirements ontology initially created during requirements engineering is iteratively refined such that test-cases can be generated automatically. An industrial water process system case study illustrates the strengths of the proposed formalism. We also present an automatic test-case generation and execution tool called REBATE (REquirements Based Automatic Testing Engine).

Accommodating frequent product changes in a short period of time is a challenging task due to limitations of the contemporary engineering approach to design, build and reconfigure automation systems. In particular, the growing quantity and diversity of manufacturing information, and the increasing need to exchange and reuse this information in an efficient way has become a bottleneck. To improve the engineering process, digital manufacturing and Product, Process and Resource (PPR) modelling are considered very promising to compress development time and engineering cost by enabling efficient design and reconfiguration of manufacturing resources. However, due to ineffective coupling of PPR data, design and reconfiguration of assembly systems are still challenging tasks due to the dependency on the knowledge and experience of engineers. This paper presents an approach for data models integration that can be employed for coupling the PPR domain models for matching the requirements of products for assembly automation. The approach presented in this paper can be used effectively to link data models from various engineering domains and engineering tools. For proof of concept, an example implementation of the approach for modelling and integration of PPR for a Festo test rig is presented as a case study.

Design of mechatronic systems involves the use of multiple disciplines, from mechanics to electronics and computer science. Different granularities of hybrid co-simulations with increasing details can be used during the design process. However, there is the need of modeling tools for effectively managing the necessary abstraction layers. This work proposes a combination of Aspect-Oriented and Object-Oriented modeling for reaching the goal. Moreover, it shows how the utilization of these tools can facilitate design-space exploration, segregation of domains of expertise and enhances co-design.