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

Methods for Semantic Interoperability in AutomationML-based Engineering

Industrial engineering is an interdisciplinary activity that involves human experts from various technical backgrounds working with different engineering tools. In the era of digitization, the engineering process generates a vast amount of data. To store and exchange such data, dedicated international standards are developed, including the XML-based data format AutomationML (AML). While AML provides a harmonized syntax among engineering tools, the semantics of engineering data remains highly heterogeneous. More specifically, the AML models of the same domain or entity can vary dramatically among different tools that give rise to the so-called semantic interoperability problem. In practice, manual implementation is often required for the correct data interpretation, which is usually limited in reusability. Efforts have been made for tackling the semantic interoperability problem. One mainstream research direction has been focused on the semantic lifting of engineering data using Semantic Web technologies. However, current results in this field lack the study of building complex domain knowledge that requires a profound understanding of the domain and sufficient skills in ontology building. This thesis contributes to this research field in two aspects. First, machine learning algorithms are developed for deriving complex ontological concepts from engineering data. The induced concepts encode the relations between primitive ones and bridge the semantic gap between engineering tools. Second, to involve domain experts more tightly into the process of ontology building, this thesis proposes the AML concept model (ACM) for representing ontological concepts in a native AML syntax, i.e., providing an AML-frontend for the formal ontological semantics. ACM supports the bidirectional information flow between the user and the learner, based on which the interactive machine learning framework AMLLEARNER is developed. Another rapidly growing research field devotes to develop methods and systems for facilitating data access and exchange based on database theories and techniques. In particular, the so-called Query By Example (QBE) allows the user to construct queries using data examples. This thesis adopts the idea of QBE in AML-based engineering by introducing the AML Query Template (AQT). The design of AQT has been focused on a native AML syntax, which allows constructing queries with conventional AML tools. This thesis studies the theoretical foundation of AQT and presents algorithms for the automated generation of query programs. Comprehensive requirement analysis shows that the proposed approach can solve the problem of semantic interoperability in AutomationML-based engineering to a great extent

A Mapping Approach to Convert MTPs into a Capability and Skill Ontology

Being able to quickly integrate new equipment and functions into an existing plant is a major goal for both discrete and process manufacturing. But currently, these two industry domains use different approaches to achieve this goal. While the Module Type Package (MTP) is getting more and more adapted in practical applications of process manufacturing, so-called skill-based manufacturing approaches are favored in the context of discrete manufacturing. The two approaches are incompatible because their models feature different contents and they use different technologies. This contribution provides a comparison of the MTP with a skill-based approach as well as an automated mapping that can be used to transfer the contents of an MTP into a skill ontology. Through this mapping, an MTP can be semantically lifted in order to apply functions like querying or reasoning. Furthermore, machines that were previously described using two incompatible models can now be used in one production process

Kommunikation und Bildverarbeitung in der Automation

In diesem Open Access-Tagungsband sind die besten Beiträge des 11. Jahreskolloquiums "Kommunikation in der Automation" (KommA 2020) und des 7. Jahreskolloquiums "Bildverarbeitung in der Automation" (BVAu 2020) enthalten. Die Kolloquien fanden am 28. und 29. Oktober 2020 statt und wurden erstmalig als digitale Webveranstaltung auf dem Innovation Campus Lemgo organisiert. Die vorgestellten neuesten Forschungsergebnisse auf den Gebieten der industriellen Kommunikationstechnik und Bildverarbeitung erweitern den aktuellen Stand der Forschung und Technik. Die in den Beiträgen enthaltenen anschauliche Anwendungsbeispiele aus dem Bereich der Automation setzen die Ergebnisse in den direkten Anwendungsbezug

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

Semantic Systems. The Power of AI and Knowledge Graphs

This open access book constitutes the refereed proceedings of the 15th International Conference on Semantic Systems, SEMANTiCS 2019, held in Karlsruhe, Germany, in September 2019. The 20 full papers and 8 short papers presented in this volume were carefully reviewed and selected from 88 submissions. They cover topics such as: web semantics and linked (open) data; machine learning and deep learning techniques; semantic information management and knowledge integration; terminology, thesaurus and ontology management; data mining and knowledge discovery; semantics in blockchain and distributed ledger technologies

A Design Science Research Approach to Architecting and Developing Information Systems for Collaborative Manufacturing : A Case for Human-Robot Collaboration

Konseptointi- ja suunnitteluvaiheessa sekä valmistuksen, käytön ja kehitysprosessin aikana syntyy tietoa, jonka hyödyntämisessä on valtavaa potentiaalia liike-elämän ja tuotantoprosessien muuttamiseen. Neljännen teollisen vallankumouksen ytimessä oleva digitaalinen muutos tunnistaa tämän painottaen erityisesti tämän tiedon yhdistämistä toimintojen ja järjestelmien tukemiseksi läpi tuotteen elinkaareen, mitä kutsutaan digitaaliseksi säikeen kehykseksi (digital thread framework). Tämän väitöskirjan tavoitteena on kehittää ja käyttää yhtä tällaista viitekehystä ihmisen ja robotin yhteistoiminnan asiayhteydessä. Tämä kehys pyrkii vastaamaan merkittävään ongelmaan, joka liittyy mukautuvuuden ja joustavuuden abstrakteihin ominaisuuksiin. Nykyiset ihmisen ja robotin yhteistyöjärjestelmät (human-robot collaboration (HRC)) on rakennettu pääasiassa pysyviksi järjestelmiksi, jotka sivuuttavat ihmisten intuitiivisen toiminnan asettamalla heidän roolinsa yhteistyötehtävissä etukäteen määritellyiksi. Lisäksi järjestelmien kyky vaihtaa tuotteesta toiseen on rajoittunutta. Tämä on erityisen ongelmallista nykyisellä laajan tuotevalikoiman aikakaudella, joka johtuu asiakkaiden räätälöidyistä vaatimuksista. Tähän taustaan vastaten, tämä väitöskirja käyttää design science research methodology -menetelmää suunnitellakseen, kehittääkseen ja ottaakseen käyttöön kolme pääasiallista artefaktia ihmisen ja robotin yhteistyösolussa laboratorioympäristössä. Ensimmäinen on digitaalisen säikeen kehys (digital thread framework), joka integroi tuotesuunnitteluympäristön toimijaksi monitoimijajärjestelmään käyttäen uusimpia tietoon perustuvia suunnittelujärjestelmiä, mikä tarjoaa prosessin toimijoille pääsyn tuotesuunnittelumalleihin reaaliajassa. Toinen on lisätyn todellisuuden malli, joka tarjoaa rajapinnan kokoonpanotehtävässä yhteistyöhön osallistuvan ihmisoperaattorin ja edellä mainitun kehyksen välille. Kolmas on tukitietomalli, jota yhteistyötä tekevät toimijat käyttävät tietopohjanaan täyttääkseen yhteistyössä tapahtuvan kokoonpanon tavoitteet mukautuvasti. Näitä kehitettyjä artefakteja käytettiin kokonaisuutena tapaustutkimuksissa, jotka liittyivät aidon dieselmoottorin kokoonpanoon, ja joissa todennettiin niiden hyödyllisyys ja että ne lisäävät joustavuutta, jota varten kehys (framework) suunniteltiin. Rajauslaatikoiden näyttäminen skaalautuvana informaationa, joka hahmottaa alikokoonpanon osien geometriaa, demostroi kehitettyjen artefaktien käytettävyyttä yhteistyötä tekevien toimijoiden aikomuksia heijastavien laajennetun todellisuuden projektioiden tuottamiseksi. Yhteenvetona tämän väitöskirjan tuloksena syntyi lähestymistapa älykkään ja mukautuvan robotiikan toteuttamiseksi hyödyntäen tietovirtoja ja mallinnusta ihmisen ja robotin yhteistoiminnan kontekstissa. Teollisuuden raportoima älykkäästi mukautuvien HRC-järjestelmien puute taas toimi osaltaan motivaationa tähän väitöskirjassa tehtyyn työhön. Kun tulevaisuuden tuotteet ja tuotantojärjestelmät muuttuvat monimutkaisemmiksi, tietojärjestelmiltä odotetaan suurempaa vastuuta korvaamaan ihmisen työmuistin luontaiset rajat ja mahdollistamaan siirtyminen kohti ihmiskeskeistä valmistusta, joihin viitataan termeillä Operator 4.0 ja Industry 5.0. Näin ollen on odotettavissa, että tietojärjestelmien tutkimus, kuten tämä väitöskirja, voi auttaa ottamaan merkittäviä askeleita tähän suuntaan.Information generated from the conceptualization, design, manufacturing, and use of a product has immense potential in transforming both the business and manufacturing processes of the manufacturing enterprise. The digital transformation at the heart of the fourth industrial revolution has acknowledged this with a special emphasis on weaving a thread of this information to support functions and systems throughout the life cycle of the product with what is known as a digital thread framework. This dissertation aims to develop and use one such framework in the context of human-robot collaborative assembly. The overarching problem that the framework aims to solve can be attributed to the abstract qualities of adaptability and flexibility. The human-robot collaboration (HRC) systems of today are built predominantly as static systems and ignore the intuitive role of humans by having their roles in collaborative tasks pre-defined. Furthermore, their ability to switch between products during product changeovers is also limited. This is especially problematic in the current era of product variety, stemming from the customised requirements of customers. To this end, this dissertation employs the design science research methodology to design, develop, and deploy predominantly three artefacts in a human-robot work cell in a laboratory setting. The first is the digital thread framework that integrates the product design environment using state-of-the-art knowledge-based engineering systems, as an agent of a multi-agent system, which provide the collaborative human-robot agents with access to product design models at run time. The second is a constituent mixed-reality model that provides an interface for the foregoing framework for the human operator engaged in collaborative assembly. The third is a supporting information model that the agents use as their knowledge base to fulfil adaptively the goals of collaborative assembly. Together, these developed artefacts were employed in case studies involving a real diesel engine assembly during which they were observed to provide utility and support the cause of adaptability for which the framework was designed. The identification of bounding boxes as a scalable information construct, that approximates the part geometry of the sub-assembly components, demonstrates the utility of the developed artefacts for spatially augmenting them as projections as intentions of collaborating agents. In summary, this dissertation contributes with an approach towards realising intelligent and adaptive robotics within the realms of information flows and modelling in the context of human-robot collaboration. The lack of intelligently adaptable HRC systems reported by the industry in part motivated the work undertaken in this dissertation. As future products and production systems become more complex, information systems are expected to assume greater responsibility to compensate for the inherent limits of the human working memory and enable transition towards a human-centred manufacturing, the current likes of which are labelled as Operator 4.0 and Industry 5.0. Thus, the expectation is that information systems research, such as this dissertation, can help take significant strides forward in this direction

PolyVR - A Virtual Reality Authoring Framework for Engineering Applications

Die virtuelle Realität ist ein fantastischer Ort, frei von Einschränkungen und vielen Möglichkeiten. Für Ingenieure ist dies der perfekte Ort, um Wissenschaft und Technik zu erleben, es fehlt jedoch die Infrastruktur, um die virtuelle Realität zugänglich zu machen, insbesondere für technische Anwendungen. Diese Arbeit bescheibt die Entstehung einer Softwareumgebung, die eine einfachere Entwicklung von Virtual-Reality-Anwendungen und deren Implementierung in immersiven Hardware-Setups ermöglicht. Virtual Engineering, die Verwendung virtueller Umgebungen für Design-Reviews während des Produktentwicklungsprozesses, wird insbesondere von kleinen und mittleren Unternehmen nur äußerst selten eingesetzt. Die Hauptgründe sind nicht mehr die hohen Kosten für professionelle Virtual-Reality-Hardware, sondern das Fehlen automatisierter Virtualisierungsabläufe und die hohen Wartungs- und Softwareentwicklungskosten. Ein wichtiger Aspekt bei der Automatisierung von Virtualisierung ist die Integration von Intelligenz in künstlichen Umgebungen. Ontologien sind die Grundlage des menschlichen Verstehens und der Intelligenz. Die Kategorisierung unseres Universums in Begriffe, Eigenschaften und Regeln ist ein grundlegender Schritt von Prozessen wie Beobachtung, Lernen oder Wissen. Diese Arbeit zielt darauf ab, einen Schritt zu einem breiteren Einsatz von Virtual-Reality-Anwendungen in allen Bereichen der Wissenschaft und Technik zu entwickeln. Der Ansatz ist der Aufbau eines Virtual-Reality-Authoring-Tools, eines Softwarepakets zur Vereinfachung der Erstellung von virtuellen Welten und der Implementierung dieser Welten in fortschrittlichen immersiven Hardware-Umgebungen wie verteilten Visualisierungssystemen. Ein weiteres Ziel dieser Arbeit ist es, das intuitive Authoring von semantischen Elementen in virtuellen Welten zu ermöglichen. Dies sollte die Erstellung von virtuellen Inhalten und die Interaktionsmöglichkeiten revolutionieren. Intelligente immersive Umgebungen sind der Schlüssel, um das Lernen und Trainieren in virtuellen Welten zu fördern, Prozesse zu planen und zu überwachen oder den Weg für völlig neue Interaktionsparadigmen zu ebnen

Model-Based Engineering of Collaborative Embedded Systems

This Open Access book presents the results of the "Collaborative Embedded Systems" (CrESt) project, aimed at adapting and complementing the methodology underlying modeling techniques developed to cope with the challenges of the dynamic structures of collaborative embedded systems (CESs) based on the SPES development methodology. In order to manage the high complexity of the individual systems and the dynamically formed interaction structures at runtime, advanced and powerful development methods are required that extend the current state of the art in the development of embedded systems and cyber-physical systems. The methodological contributions of the project support the effective and efficient development of CESs in dynamic and uncertain contexts, with special emphasis on the reliability and variability of individual systems and the creation of networks of such systems at runtime. The project was funded by the German Federal Ministry of Education and Research (BMBF), and the case studies are therefore selected from areas that are highly relevant for Germany’s economy (automotive, industrial production, power generation, and robotics). It also supports the digitalization of complex and transformable industrial plants in the context of the German government's "Industry 4.0" initiative, and the project results provide a solid foundation for implementing the German government's high-tech strategy "Innovations for Germany" in the coming years