An ontology for CAD data and geometric constraints as a link between product models and semantic robot task descriptions

Perzylo, Alexander; Somani, Nikhil; Rickert, Markus; Knoll, Alois

doi:10.1109/iros.2015.7353971

Cited by 54 publications

(40 citation statements)

References 9 publications

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“…Parts of the proposed architecture and ecosystem have already been published. In [3], we present an ontology for describing CAD models in a semantic way based on the boundary representation (BREP) paradigm, in which the mathematical models of geometries are described instead of being approximated via polygons. One of the core applications of our semantic digital twins, is the automatic identification of suitable resources for a given semantic model of an industrial manufacturing process.…”

Section: Related Workmentioning

confidence: 99%

“…For describing geometric properties of products and manufacturing resources alike, we rely on our OntoBREP ontology [3]. As the name implies, the ontology follows a BREP paradigm, in which faces, edges, and vertices are typically specified by defining an infinite geometry and corresponding bounds that make it finite.…”

Section: Geometry Modelsmentioning

confidence: 99%

“…For instance, this can be used to geometrically describe regions of interest on a device, e.g., where to put a workpiece or which areas to avoid due to moving parts. In assembly specifications, the OntoBREP-based representation can be combined with semantically specified geometric interrelational constraints [3], e.g., stating that two faces must be coincident after a particular assembly step. brep:a11 "1.0"ˆˆxsd:double, brep:a12 "0.0"ˆˆxsd:double, ... brep:a44 "1.0"ˆˆxsd:double…”

Section: Geometry Modelsmentioning

confidence: 99%

“…In this paper, we propose a semantic description language for OPC UA NodeSets based on the Web Ontology Language (OWL) 3 . As the OWL formalism is based on description logics, OWL-based descriptions can be automatically interpreted by reasoning components, which are able to check the logical consistency of the models and derive implicit facts through logical inference.…”

Section: Introductionmentioning

confidence: 99%

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OPC UA NodeSet Ontologies as a Pillar of Representing Semantic Digital Twins of Manufacturing Resources

Perzylo

Profanter

Rickert

et al. 2019

2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)

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The effectiveness of cognitive manufacturing systems in agile production environments heavily depends on the automatic assessment of various levels of interoperability between manufacturing resources. For taking informed decisions, a semantically rich representation of all resources in a workcell or production line is required. OPC UA provides means for communication and information exchange in such distributed settings. This paper proposes a semantic representation of a resource's properties, in which we use OWL ontologies to encode the information models that can be found in OPC UA NodeSet specifications. We further combine these models with an OWLbased description of the resource's geometry and-if applicable-its kinematic model. This leads to a comprehensive semantic representation of hardware and software features of a manufacturing resource, which we call semantic digital twin. Among other things, it reduces costs through virtual prototyping and enables the automatic deployment of manufacturing tasks in production lines. As a result, small-batch assemblies become financially viable. In order to minimize the effort of creating OWL-based UA NodeSet descriptions, we provide a software tool for the automatic transformation of XML-based NodeSet specifications that adhere to the OPC Foundation's NodeSet2 XML schema.

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Section: Related Workmentioning

confidence: 99%

Section: Geometry Modelsmentioning

confidence: 99%

Section: Geometry Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

OPC UA NodeSet Ontologies as a Pillar of Representing Semantic Digital Twins of Manufacturing Resources

Perzylo

Profanter

Rickert

et al. 2019

2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)

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“…Looking at the literature on manufacturing ontologies, research efforts can be roughly classified in two broad segments: the first one aimed at establishing the conceptual and formal foundations of manufacturing ontologies (Bock et al, 2010;Borgo and Leitão, 2007;Grüninger, 2009;Usman et al, 2013), and the second one specifically focused on the use of ontologies in application systems (Colombo et al, 2007;Matsokis and Kiritsis, 2010;Perzylo et al, 2015;Tessier and Wang, 2013;Terkaj et al, 2012). Unfortunately, the two research lines have been co-existing for a long time with only little interaction.…”

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confidence: 99%