Now showing 1 - 5 of 5
  • Publication
    Metadata only
    A Formal Capability and Skill Model for Use in Plug and Produce Scenarios
    (IEEE, 2020-09-01) ;
    Hildebrandt, Constantin
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    Manufacturing companies face an environment that is dominated by influences which affect the usage of their manufacturing equipment. Trends like shortening life cycles of products, increasing numbers of product variants and the resulting decrease in lot sizes put pressure on companies' operations. Existing machines have to be adaptable to provide a high degree of flexibility and new machines have to be easily integrated into an existing plant in a plug and produce fashion. Research contributions that focus on a higher level description of machine functionalities are seen as a promising approach to cope with the aforementioned challenges. While there exists quite a large amount of contributions on this topic, these contributions focus either on formal models or on executable functions. The developed models mostly represent project specific contents and are rarely based on industry standards.In this contribution, we present an approach to a formal model of machine capabilities that directly includes a description of executable skills. The presented capability and skill model is based on a variety of separate so-called ontology design patterns that contain the vocabulary of industry standards and therefore provide a profound knowledge which is agreed upon by a large community. In addition to the description of our model, this contribution shows how these models can be used in order to achieve simple and rapid integration of new manufacturing modules and their capabilities.
  • Publication
    Metadata only
    Ontology building for cyber-physical systems: application in the manufacturing domain
    (IEEE, 2020-07-01)
    Hildebrandt, Constantin
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    Kustner, Christof
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    Lopez-Enriquez, Carlos Manuel
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    Muller, Andreas W.
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    Caesar, Birte
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    Gundlach, Claas Steffen
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    Cyber-physical systems (CPSs) in the manufacturing domain can be deployed to support monitoring and analysis of production systems of a factory in order to improve, support, or automate processes, such as maintenance or scheduling. When a network of CPS is subject to frequent changes, the semantic interoperability between the CPSs is of special interest in order to avoid manual, tedious, and error-prone information model alignments at runtime. Ontologies are a suitable technology to enable semantic interoperability, as they allow the building of information models that lank machine-readable meaning to information, thus enabling CPSs to mutually understand the shared information. The contribution of this article is twofold. First, we present an ontology building method that is tailored toward the needs of CPSs in the manufacturing domain. For this purpose, we introduce the requirements regarding this method and discuss related research concerning ontology building. The method itself is designed to begin with ontological requirements and to yield a formal ontology. As the reuse of ontologies and other information resources (IRs) is crucial to the success of ontology building projects, we put special emphasis on how to reuse IRs in the CPS domain. Second, we present a reusable set of ontology design patterns that have been developed with the aforementioned method in an industrial use case and illustrate their application in the considered industrial environment. The contribution of this article extends the method introduced, as a postconference paper, by a detailed industrial application. Note to Practitioners-With growing digitalization in industry, the exchange and use of manufacturing-related data are becoming increasingly important to improve, support, or automate processes. Thus, it is necessary to combine information from different data sources that have been designed by different vendors and may, therefore, be heterogeneous in structure and semantics. A system that plans a maintenance worker's daily schedule, for instance, requires information about the status of machines, production plans, and inventory, which resides in other systems, such as programmable logic controllers (PLCs) or databases. When creating such information systems, accessing, searching, and understanding the different data sources is a time-intensive and error-prone procedure due to the heterogeneities of the data sources. Even worse, this procedure has to be repeated for every newly built system and for every newly introduced data source. To allow for eased access, searching, and understanding of these heterogeneous data sources, ontology can be used to integrate all heterogeneous data sources in one schema. This article contributes a method for building such ontologies in the manufacturing domain. Furthermore, a set of ontology design patterns is presented, which can be reused when building ontologies for a domain.
  • Publication
    Metadata only
    Offenes, webbasiertes Werkzeug zur Informationsmodellierung mit Formalisierter Prozessbeschreibung
    (VDI Verlag, 2020) ; ;
    Hildebrandt, Constantin
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    Beim Engineering automatisierter Anlagen müssen Experten unterschiedlicher Gewerke möglichst effizient zusammenarbeiten. Diese Zusammenarbeit kann durch eine für alle Beteiligten verständliche Modellierung der zu automatisierenden Prozesse erleichtert werden. Die VDI/VDE-Richtlinie 3682 "Formalisierte Prozessbeschreibungen" definiert ein solches Beschreibungsmittel, das zur Modellierung unterschiedlicher Arten von Prozessen genutzt werden kann. Da die Richtlinie mit einer geringen Menge an Modellelementen auskommt, kann sie auch ohne großen Einarbeitungsaufwand bspw. im Rahmen von Workshops genutzt werden. Um solche Prozessmodelle digital zu erfassen und auszutauschen, wird jedoch ein entsprechendes Software-Werkzeug benötigt. Bislang gab es nur sehr wenige solcher Werkzeuge, mit denen Prozesse entsprechend der Formalisierten Prozessbeschreibung modelliert werden können. Diese Werkzeuge sind heute nicht mehr verfügbar, besitzen kein offenes Datenmodell und lassen sich weder leicht nutzen noch in andere Software integrieren. Dieser Beitrag versucht diese Lücke zu schließen, indem er ein offenes, webbasiertes Werkzeug zur Modellierung gemäß der Formalisierten Prozessbeschreibung präsentiert. Der gesamte Quellcode des Werkzeugs ist frei verfügbar und kann eingesehen, verwendet und weiterentwickelt werden. Zur einfachen Nutzung wird eine Softwareversion angeboten, die ohne jeglichen Einrichtungsaufwand zur Modellierung von Prozessen genutzt werden kann.
  • Publication
    Metadata only
    Automating the Development of Machine Skills and their Semantic Description
    (IEEE, 2020) ;
    Hildebrandt, Constantin
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    Caesar, Birte
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    Bakakeu, Jupiter
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    Peschke, Jörn
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    Scholz, André
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    In order to approach the vision of quickly integrating new machines and their functionalities into a production plant, machines have to provide a machine-readable description of themselves and their functionalities. With such a description, it becomes possible to find required functions, check compatibility and, finally, execute production processes. In recent years, semantic web technologies have proven to be a promising enabler to realize such descriptions in the form of ontologies. But the creation of such an ontological description is an additional, tedious and error-prone task for a machine developer who might most likely not be an expert in semantic web technologies. In order to support developers in implementing machine function-alities as semantically described skills, we developed a method that highly automates all additional ontology-related tasks. The presented method makes use of information already contained in engineering artifacts, helps in adding additional information, and provides a framework to implement skill behavior. By using the proposed method, machine developers are put in a position to develop formal capability models themselves and with little additional effort.
  • Publication
    Metadata only
    Context-sensitive reconfiguration of collaborative manufacturing systems
    (Elsevier, 2019)
    Caesar, Birte
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    Nieke, Michael
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    Hildebrandt, Constantin
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    Seidl, Christoph
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    Schäfer, Ina
    To stay competitive in a highly dynamic environment, manufacturing companies have to quickly react to changing customer demands. Manufacturing systems may only serve demands that are covered by their capabilities. The manufacturability of a product can be analyzed by comparing the provided capabilities against the product’s requirements. The manufacturing capabilities depend on the current system and subsystem configuration. If a product cannot be manufactured, first, it must be analyzed whether any valid configuration exists that provides the required capabilities, and second, the system has to be reconfigured according to the new configuration. To the best of our knowledge no existing method exists that enables these previously mentioned steps. In this paper, we introduce a method for context-sensitive reconfiguration of multiple collaborating manufacturing systems that might come from different vendors to create a customized product on demand. We utilize variability models to capture the possible configuration space and describe influences of product properties on features of the variability model by providing a context-sensitive variability model. We apply our method to a demonstrator and show that we enable modeling of reconfigurable manufacturing systems that are automatically reconfigured on context change.