ScienceDirect IFAC-PapersOnLine 48-3 (2015) 916–923 Available online at www.sciencedirect.com 2405-8963 © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. Peer review under responsibility of International Federation of Automatic Control. 10.1016/j.ifacol.2015.06.200 © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. Towards Effective Management of Inconsistencies in Model-Based Engineering of Automated Production Systems Stefan Feldmann 1 , Sebastian J. I. Herzig 2 , Konstantin Kernschmidt 1 , Thomas Wolfenstetter 3 , Daniel Kammerl 4 , Ahsan Qamar 2 , Udo Lindemann 4 , Helmut Krcmar 3 , Christiaan J. J. Paredis 2 , Birgit Vogel-Heuser 1 1 Institute of Automation and Information Systems, Technische Universität München, Garching, Germany (e-mail: feldmann@ais.mw.tum.de, kernschmidt@ais.mw.tum.de, vogel-heuser@ais.mw.tum.de) 2 Model-Based Systems Engineering Center, Georgia Institute of Technology, Atlanta, Georgia, United States of America (e-mail: sebastian.herzig@gatech.edu, ahsan.qamar@gatech.edu, chris.paredis@me.gatech.edu) 3 Chair for Information Systems, Technische Universität München, Munich, Germany (e-mail: thomas.wolfenstetter@in.tum.de, krcmar@in.tum.de) 4 Institute of Product Development, Technische Universität München, Munich, Germany (e-mail: daniel.kammerl@pe.mw.tum.de, lindemann@pe.mw.tum.de) Abstract: The development of automated production systems requires the collaborative effort of a variety of stakeholders from different disciplines. In model-based systems engineering, stakeholders address their specific concerns by forming a number of views using models. Because of the multi- disciplinary nature of automated production systems, a variety of modelling languages, formalisms and tools is typically employed. Nevertheless, the aggregation of models is nowadays limited by the communication between stakeholders and interdisciplinary understanding. Therefore, in order to achieve a positive outcome of the design process it is crucial that the models are free of inconsistencies. As a first step, this paper describes challenges related to managing inconsistencies in models of systems from the domain of automated production systems. A conceptual approach that uses semantic web technologies and a technology demonstrator illustrating the technical viability of the approach are shown. Finally, requirements for a discipline-spanning inconsistency management framework are derived based on the presented challenges and initial findings from applying the approach to a demonstration case. Keywords: Model management, inconsistency management, multi-disciplinary engineering, ontologies 1. INTRODUCTION During the development of automated production systems, a multitude of stakeholders from different disciplines is involved. These stakeholders address their specific concerns by forming views on the system. To adequately address these concerns, a variety of different formalisms, modelling languages and tools is necessary (Broy et al., 2010). Crucial to achieving a positive outcome of the automated production system design is that the models are free of inconsistencies. In current practice, support for checking conformance to syntactical and well-formedness constraints is provided by most tools, but only to a limited extent. In automated production systems engineering, potentially arising design flaws are identified during the process of verification and validation. Since verification and validation are typically performed in later engineering phases (Isermann, 2008) and infrequently, identifying and resolving some inconsistencies can be very costly. Therefore, we argue that an automated and continuous strategy for inconsistency management adds significant value to verification and validation processes in the automated production systems domain. On this account, section 2 introduces a simple representative demonstration case for an automated production system. Using this demonstration case, we describe challenges related to managing inconsistencies in models of automated production systems (section 3). Section 4 provides a brief overview on related literature. Following that, our conceptual approach and a technology demonstrator developed to illustrate the viability of the approach, are presented (section 5). Based on the presented challenges and the initial findings from applying our approach to an example scenario, requirements for a discipline-spanning inconsistency management framework are derived (section 6). The paper closes with a summary and directions for future research. 2. DEMONSTRATION CASE In the following, we introduce a simple demonstration case: a Pick-and-Place Unit (PPU) (see Fig. 1). Although being a bench-scale, academic demonstration case, the PPU is complex enough to demonstrate the challenges that arise in model-based engineering of automated production systems (Vogel-Heuser et al., 2014). The PPU consists of four modules: a stack, a crane, a stamp and a ramp. The stack represents the source of work pieces (WPs). In a first step, a WP is pushed from the stack into the handover position. The crane then grabs the WP and transports the WP to the stamp, where it is clamped and stamped. After being released again, the crane transports the WP to the ramp.