To cope with the challenge of managing the complexity of automated production systems, model-based approaches are applied increasingly. However, due to the multitude of different disciplines involved in automated production systems engineering, e.g., mechanical, electrical, and software engineering, several modeling languages are used within a project to describe the system from different perspectives. To ensure that the resulting system models are not contradictory, the necessity to continuously diagnose and handle inconsistencies within and in between models arises. This article proposes a comprehensive approach that allows stakeholders to specify, diagnose, and handle inconsistencies in model-based systems engineering. In particular, to explicitly capture the dependencies and consistency rules that must hold between the disparate engineering models, a dedicated graphical modeling language is proposed. By means of this language, stakeholders can specify, diagnose, and handle inconsistencies in the accompanying inconsistency management framework. The approach is implemented based on the Eclipse Modeling Framework (EMF) and evaluated based on a demonstrator project as well as a small user experiment. First findings indicate that the approach is expressive enough to capture typical dependencies and consistency rules in the automated production system domain and that it requires less effort compared to manually developing inter-model inconsistency management solutions. (C) 2019 Elsevier Inc. All rights reserved.

Adaptive and flexible production systems require modular, reusable software as a prerequisite for their long-term life cycle of up to 50 years. We introduce a benchmark process to measure software maturity for industrial control software of automated production systems.

Over the past years, the design of production systems has changed rapidly towards complex mechatronic systems, tightly integrating mechanics, electronics and software. The development of such integrated systems requires new approaches to cope with this challenge in order to ensure the desired design and functionality of the system. This article analyses how the required information from different disciplines can be handled appropriately by the engineers. Therefore, a model-based framework is presented, which supports the interdisciplinary development process. It is based on the modelling language SysML and enables the integration of standardised properties through model libraries. Furthermore, the resulting model from the development phase can be used to analyse possible interdisciplinary impacts in the case of required changes. A case study is presented to evaluate the applicability of the proposed framework.

The complexity of automated production systems increases steadily – especially due to the rising customer demand to manufacture individualized goods. To stay competitive, companies in this domain need to adapt their engineering to deliver machines and plants with higher quality in shorter time. Hence, to reduce design errors and identify problems already in early engineering stages, it is essential to ensure that the disparate engineering models – e.g., from mechanical, electrical and software engineering – are free from inconsistencies. This paper presents a concept for inter-model inconsistency management. In particular, the proposed concept provides an interactive visualization approach that captures the dependencies between the different engineering models explicitly and visualizes them to the involved stakeholders. By that, the location of and cause for inconsistencies can be identified more easily; dependencies between the different engineering disciplines can be visualized in a comprehensive manner.

Especially due to the ever-increasing complexity of automated production systems, model-based systems engineering (MBSE) is gaining more and more importance. Nevertheless, system models do not stand for themselves - rather, they are related to a multitude of engineering documents such as requirements specification documents, CAD drawings or electric circuit diagrams. Especially for practical applications, it is therefore essential to couple system models with such engineering documents. As a basis to overcome this issue, this paper proposes a concept for coupling models and documents in automated production systems at the example of requirements engineering models. The concept envisions an automatic generation process from such models to textual Functional Specification Documents (FSDs), which are often used throughout negotiation between manufacturers and customers. Changes to such FSDs, e.g. made via PDF annotation tools, are then propagated back to the respective models. We envision the concept to be a basis for future extensions that aim at improving current MBSE approaches to make them more productive and attractive for practical applications during engineering of automated production systems.

This material serves as supplementary material for the paper A Comprehensive Approach for Managing Inter-Model Inconsistencies in Automated Production Systems Engineering, which has been submitted to IEEE CASE 2016.

Control software in the automated production systems domain is becoming increasingly complex. As a consequence, appropriate methods to improve control software quality need to be identified. Although sophisticated frameworks and tools for software quality improvement exist in the computer science domain, support for industrial control software development is still limited. As a first step towards addressing this issue, this paper proposes an analysis framework that aims at evaluating control software by means of Semantic Web technologies.

Current market dynamics force today's companies to manufacture smaller lot sizes up to individual products. As a consequence, companies need to react to such changes; it is hence inevitable to ensure a correct, reliable and flexible engineering process, which allows for managing the highly variant-rich machines. This article investigates the applicability of interdisciplinary product lines for the engineering in the machine manufacturing domain. Therein, four core aspects are addressed: first, the current practice of companies regarding the management of variants is analysed. Second, the requirements to be fulfilled by an interdisciplinary variant management approach are analysed. Third, an interdisciplinary product line approach is presented that aims at overcoming the challenges. Fourth, the benefits and limitations of the approach are discussed and research gaps that need to be addressed in future works are identified.

Well-structured control software provides the means to reuse existing code and to save time and money. However, there is often scope for optimization, e.g. due to the need for pragmatic adaptations before or during the commissioning phase, as well as due to growing software structures. Appropriate tool support is currently lacking in the machine and plant manufacturing domain to achieve a better software structure. This article introduces a concept and a prototypical support tool by means of Semantic Web Technologies, which allow for the structural analysis of control software.

In this contribution we point out the challenges in Model-Based development of industrial plants regarding the integration of requirements. With the case study of a conveyor sorting system for parcels we show (i) that the specification of requirements is usually still only text based and (ii) what difficulties are entailed with that approach. The conceivable benefits of a Model-Based requirements engineering approach in the machinery and plant building industry are explained and compared to the state of the art requirements modeling techniques of other technical fields. Although, our proposed Model- Based requirements engineering approach points into the right direction, some shortcomings still remain. They have to be solved in the future work to enable a seamless Model- Based development from the requirements to detail design of industrial plants and other complex mechatronic systems.

This material serves as supplementary material for the paper Analysis Framework for Evaluating PLC Software: An Application of Semantic Web Technologies, which has been submitted to IEEE ISIE 2016.

Gut strukturierte Steuerungssoftware hilft, bewährten Code wiederzuverwenden und somit Zeit und Geld zu sparen. Oftmals gibt es jedoch Optimierungspotenziale, zum Beispiel durch die Notwendigkeit pragmatischer Anpassungen vor beziehungsweise bei der Inbetriebnahme oder durch gewachsene Softwarestrukturen. Um zu einer besseren Softwarestruktur zu gelangen, fehlt es jedoch zumeist an Werkzeugunterstützung im Maschinen- und Anlagenbau. Dieser Beitrag zeigt ein Konzept und eine prototypische Werkzeugunterstützung mittels Semantic-Web-Technologien auf, die die strukturelle Analyse von Steuerungssoftware ermöglichen.

The systematic management of the various models in automated production systems engineering is a major challenge as, due to the multi-disciplinary nature, different stakeholders provide their potentially heterogeneous but partially overlapping descriptions of the system. This leads to the need of ensuring inter-model consistency by managing occurring inconsistencies. In previous work, existing approaches have been surveyed; however, none is providing a comprehensive approach for dealing with inconsistencies in multi-disciplinary systems engineering. Therefore, we propose in this paper a comprehensive but at the same time light-weight approach for specifying and managing inter-model consistency. In particular, inter-model consistency is explicitly modelled and, hence, allows to detect, represent, and manage inconsistencies. Concerning the latter, we provide an interactive and collaborative approach to automate the consistency maintenance during model evolution, which is especially needed in multi-disciplinary projects.

Inconsistencies that occur during mechatronic systems engineering can be expensive - especially when identified too late. The challenge to specify and diagnose inconsistencies in the manifold models of the mechatronic system under study therein mainly results from the heterogeneity of the different disciplines. As a consequence, this article analyses the requirements on the specification and diagnosis of inconsistencies from a research perspective and proposes a concept for a knowledge-based framework. Therein, Semantic Web Technologies are being used, as their flexibility and extensibility is especially useful for heterogeneous models. By means of a use case, the findings are illustrated from a practical perspective and the strengths and limitations of such an approach are discussed.

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.

Gute Modularisierung von Steuerungssoftware im Maschinen- und Anlagenbau hilft bewahrten Code auch bei vollig neuen Entwicklungen wiederzuverwenden und so Zeit und Geld zu sparen. Durch die Notwendigkeit pragmatischer Anpassungen vor oder bei der Inbetriebnahme oder durch uber Jahrzehnte gewachsene Strukturen gibt es oftmals in vielen Unternehmen auf diesem Gebiet Optimierungspotentiale. Um zu einer besseren Softwarestruktur zu gelangen fehlt jedoch die Werkzeugunterstutzung. In diesem Beitrag wird ein Konzept fur eine graphenbasierte Programmanalyse vorgestellt, mit dessen Hilfe die Untersuchung und Verbesserung der Modularitat und damit der Wiederverwendbarkeit von SPS-Programmen und den dazugehorigen Modulbibliotheken unterstutzt wird. Durch Uberfuhren der Programme und Bibliotheken in ein Abhangigkeitsmodell konnen effizient Algorithmen zur Errechnung von Kennwerten eingesetzt werden, um potentielle Modulkandidaten oder kritische, besonders komplexe Strukturen aufzudecken. Zur Unterstutzung der manuellen, explorativen Auswertung der Strukturen wird zudem eine Visualisierung der Abhangigkeiten vorgestellt, die mit Hilfe flexibel anpassbarer Filter- und Interaktionsmoglichkeiten noch handhabbarer wird. Anhand einiger Anwendungsbeispiele werden schlieslich mogliche Einsatzszenarien des Ansatzes vorgestellt.