Interpreting OWL Complex Classes in AutomationML based on Bidirectional Translation

The World Wide Web Consortium (W3C) has published several recommendations for building and storing ontologies, including the most recent OWL 2 Web Ontology Language (OWL). These initiatives have been followed by practical implementations that popularize OWL in various domains. For example, OWL has been used for conceptual modeling in industrial engineering, and its reasoning facilities are used to provide a wealth of services, e.g. model diagnosis, automated code generation, and semantic integration. More specifically, recent studies have shown that OWL is well suited for harmonizing information of engineering tools stored as AutomationML (AML) files. However, OWL and its tools can be cumbersome for direct use by engineers such that an ontology expert is often required in practice. Although much attention has been paid in the literature to overcome this issue by transforming OWL ontologies from/to AML models automatically, dealing with OWL complex classes remains an open research question. In this paper, we introduce the AML concept models for representing OWL complex classes in AutomationML, and present algorithms for the bidirectional translation between OWL complex classes and their corresponding AML concept models. We show that this approach provides an efficient and intuitive interface for nonexperts to visualize, modify, and create OWL complex classes.Comment: As accepted to IEEE 24th International Conference on Emerging Technologies and Factory Automation (ETFA 2019

Architecture-based Evolution of Dependable Software-intensive Systems

This cumulative habilitation thesis, proposes concepts for (i) modelling and analysing dependability based on architectural models of software-intensive systems early in development, (ii) decomposition and composition of modelling languages and analysis techniques to enable more flexibility in evolution, and (iii) bridging the divergent levels of abstraction between data of the operation phase, architectural models and source code of the development phase

Proceedings of the 2009 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory

The joint workshop of the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB, Karlsruhe, and the Vision and Fusion Laboratory (Institute for Anthropomatics, Karlsruhe Institute of Technology (KIT)), is organized annually since 2005 with the aim to report on the latest research and development findings of the doctoral students of both institutions. This book provides a collection of 16 technical reports on the research results presented on the 2009 workshop

Development of a supervisory internet of things (IoT) system for factories of the future

Big data is of great importance to stakeholders, including manufacturers, business partners, consumers, government. It leads to many benefits, including improving productivity and reducing the cost of products by using digitalised automation equipment and manufacturing information systems. Some other benefits include using social media to build the agile cooperation between suppliers and retailers, product designers and production engineers, timely tracking customers’ feedbacks, reducing environmental impacts by using Internet of Things (IoT) sensors to monitor energy consumption and noise level. However, manufacturing big data integration has been neglected. Many open-source big data software provides complicated capabilities to manage big data software for various data-driven applications for manufacturing. In this research, a manufacturing big data integration system, named as Data Control Module (DCM) has been designed and developed. The system can securely integrate data silos from various manufacturing systems and control the data for different manufacturing applications. Firstly, the architecture of manufacturing big data system has been proposed, including three parts: manufacturing data source, manufacturing big data ecosystem and manufacturing applications. Secondly, nine essential components have been identified in the big data ecosystem to build various manufacturing big data solutions. Thirdly, a conceptual framework is proposed based on the big data ecosystem for the aim of DCM. Moreover, the DCM has been designed and developed with the selected big data software to integrate all the three varieties of manufacturing data, including non-structured, semi-structured and structured. The DCM has been validated on three general manufacturing domains, including product design and development, production and business. The DCM cannot only be used for the legacy manufacturing software but may also be used in emerging areas such as digital twin and digital thread. The limitations of DCM have been analysed, and further research directions have also been discussed

An ontology-based approach for integrating engineering workflows for industrial assembly automation systems

Modern manufacturing organisations face a number of external challenges as the customer-base is more varied, more knowledgeable, and has a broader range of requirements. This has given rise to paradigms such as mass customisation and product personalisation. Internally, businesses must manage multidisciplinary teams that must work together to achieve a common goal despite spanning multiple domains, organisations, and due to improved communication technologies, countries. The motivation for this research is to therefore understand firstly how the multiplicity of stakeholders come together to realise the ever increasing and ever more complex number of product variants that manufacturing systems must now realise. The lack of integration of engineering tools and methods is identified to be one of the barriers to smooth engineering workflows and thus one of the key challenges faced in the current dynamic market. To address this problem, this research builds upon previous works that propose domain ontologies for representing knowledge in a way that is both machine and human readable, facilitating interoperability between engineering software. In addition to this, the research develops a novel Skill model that brings the domain ontologies into a practical, implementable framework that complements existing industrial workflows. The focus of this thesis is the domain of industrial assembly automation systems due to the role this stage of manufacturing plays in realising product variety. Therefore, the proposed ontological models and framework are applied to product assembly scenarios. The key contributions of this work are the consolidation of domain ontologies with a Skill model within the context of assembly systems engineering, development of a broader framework for the ontologies to sit within that complements existing workflows. In addition, the research demonstrates how the framework can be applied to connect assembly process planning activities with machine control logic to identify and rectify inconsistencies as new products are introduced. In summary, the thesis identifies the shortcomings of existing ontological models within the context of manufacturing, develops new models to address those shortcoming, and develops new, useful ways for ontological models to be used to address industrial problems by integrating them with virtual engineering tools

Consistent View-Based Management of Variability in Space and Time

Systeme entwickeln sich schnell weiter und existieren in verschiedenen Variationen, um unterschiedliche und sich ändernde Anforderungen erfüllen zu können. Das führt zu aufeinanderfolgenden Revisionen (Variabilität in Zeit) und zeitgleich existierenden Produktvarianten (Variabilität in Raum). Redundanzen und Abhängigkeiten zwischen unterschiedlichen Produkten über mehrere Revisionen hinweg sowie heterogene Typen von Artefakten führen schnell zu Inkonsistenzen während der Evolution eines variablen Systems. Die Bewältigung der Komplexität sowie eine einheitliche und konsistente Verwaltung beider Variabilitätsdimensionen sind wesentliche Herausforderungen, um große und langlebige Systeme erfolgreich entwickeln zu können. Variabilität in Raum wird primär in der Softwareproduktlinienentwicklung betrachtet, während Variabilität in Zeit im Softwarekonfigurationsmanagement untersucht wird. Konsistenzerhaltung zwischen heterogenen Artefakttypen und sichtbasierte Softwareentwicklung sind zentrale Forschungsthemen in modellgetriebener Softwareentwicklung. Die Isolation der drei angrenzenden Disziplinen hat zu einer Vielzahl von Ansätzen und Werkzeugen aus den unterschiedlichen Bereichen geführt, was die Definition eines gemeinsamen Verständnisses erschwert und die Gefahr redundanter Forschung und Entwicklung birgt. Werkzeuge aus den verschiedenen Disziplinen sind oftmals nicht ausreichend integriert und führen zu einer heterogenen Werkzeuglandschaft sowie hohem manuellen Aufwand während der Evolution eines variablen Systems, was wiederum der Systemqualität schadet und zu höheren Wartungskosten führt. Basierend auf dem aktuellen Stand der Forschung in den genannten Disziplinen werden in dieser Dissertation drei Kernbeiträge vorgestellt, um den Umgang mit der Komplexität während der Evolution variabler Systeme zu unterstützten. Das unifizierte konzeptionelle Modell dokumentiert und unifiziert Konzepte und Relationen für den gleichzeitigen Umgang mit Variabilität in Raum und Zeit basierend auf einer Vielzahl ausgewählter Ansätze und Werkzeuge aus der Softwareproduktlinienentwicklung und dem Softwarekonfigurationsmanagement. Über die bloße Kombination vorhandener Konzepte hinaus beschreibt das unifizierte konzeptionelle Modell neue Möglichkeiten, beide Variabilitätsdimensionen zueinander in Beziehung zu setzen. Die unifizierten Operationen verwenden das unifizierte konzeptionelle Modell als Datenstruktur und stellen die Basis für operative Verwaltung von Variabilität in Raum und Zeit dar. Die unifizierten Operationen werden basierend auf einer Analyse diverser Ansätze konzipiert, welche verschiedene Modalitäten und Paradigmen verfolgen. Während die unifizierten Operationen die Funktionalität von analysierten Werkzeugen abdecken, ermöglichen sie den gleichzeitigen Umgang mit beiden Variabilitätsdimensionen. Der unifizierte Ansatz basiert auf den vorhergehenden Beiträgen und erweitert diese um Konsistenzerhaltung. Zu diesem Zweck wurden Typen von variabilitätsspezifischen Inkonsistenzen identifiziert, die während der Evolution variabler heterogener Systeme auftreten können. Der unifizierte Ansatz ermöglicht automatisierte Konsistenzerhaltung für eine ausgewählte Teilmenge der identifizierten Inkonsistenztypen. Jeder Kernbeitrag wurde empirisch evaluiert. Zur Evaluierung des unifizierten konzeptionellen Modells und der unifizierten Operationen wurden Expertenbefragungen durchgeführt, Metriken zur Bewertung der Angemessenheit einer Unifizierung definiert und angewendet, sowie beispielhafte Anwendungen demonstriert. Die funktionale Eignung des unifizierten Ansatzes wurde mittels zweier Realweltfallstudien evaluiert: Die häufig verwendete ArgoUML-SPL, die auf ArgoUML basiert, einem UML-Modellierungswerkzeug, sowie MobileMedia, eine mobile Applikation für Medienverwaltung. Der unifizierte Ansatz ist mit dem Eclipse Modeling Framework (EMF) und dem Vitruvius Ansatz implementiert. Die Kernbeiträge dieser Arbeit erweitern das vorhandene Wissen hinsichtlich der uniformen Verwaltung von Variabilität in Raum und Zeit und verbinden diese mit automatisierter Konsistenzerhaltung für variable Systeme bestehend aus heterogenen Artefakttypen

Consistent View-Based Management of Variability in Space and Time

Developing variable systems faces many challenges. Dependencies between interrelated artifacts within a product variant, such as code or diagrams, across product variants and across their revisions quickly lead to inconsistencies during evolution. This work provides a unification of common concepts and operations for variability management, identifies variability-related inconsistencies and presents an approach for view-based consistency preservation of variable systems

Consistent View-Based Management of Variability in Space and Time

Developing variable systems faces many challenges. Dependencies between interrelated artifacts within a product variant, such as code or diagrams, across product variants and across their revisions quickly lead to inconsistencies during evolution. This work provides a unification of common concepts and operations for variability management, identifies variability-related inconsistencies and presents an approach for view-based consistency preservation of variable systems

Making chocolate from beans: what’s involved?

Industry differentiates between cocoa processing and chocolate manufacturing. Cocoa processing covers the activity of converting the beans into nib, liquor, butter, cake and powder. Chocolate manufacturing covers the blending and refining of cocoa liquor, cocoa butter and various optional ingredients, such as milk and sugar