An RDF-based approach for implementing industry 4.0 components with Administration Shells

Grangel-González, Irlán; Halilaj, Lavdim; Auer, Sören; Lohmann, Steffen; Lange, Christoph; Collarana, Diego

doi:10.1109/etfa.2016.7733503

Cited by 40 publications

(18 citation statements)

References 15 publications

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“…For this purpose, in the last decade, ontologies have been developed for one specific industrial domain such as aviation (Keller, 2016), aeropsace (Kossmann et al, 2009), construction (Liao et al, 2009), steel production (Dobrev et al, 2008), chemical engineering (Vinoth & Sankar, 2016;Feng et al, 2018), oil industry (Du et al, 2010;Guo & Wu, 2012), energy (Santos et al, 2018), and electronics (Liu et al, 2005a). Other ontologies have been used for one specific manufacturing process such as packaging (Liu et al, 2005b), process engineering (Wiesner et al, 2010), process compliance (Disi & Zualkernan, 2009), risk management (Atkinson et al, 2006), safety management (Hooi et al, 2012), customer feedback analysis (Kim and Lee, 2013;Daly et al, 2015), organizational management (Grangel-Gonzalez et al, 2016;Izhar and Apduhan, 2017), project management (Cheah et al, 2011), product development (Zhang et al, 2017), maintenance (Haupert et al, 2014), resource reconfiguration (Wan et al, 2018b), and production scheduling (Kourtis et al, 2019). Ontologies have also been focused on one service, for example, ticketing (Vukmirovic et al, 2006), or on one manufacturing concept, for example, information flow (Bildstein and Feng, 2018), information security (Mozzaquatro et al, 2016), and data integration (Yusupova et al).…”

Section: Industry 40 Ontological Frameworkmentioning

confidence: 99%

Ontologies for Industry 4.0

Ragavan

Khamis

Fiorini³

et al. 2019

The Knowledge Engineering Review

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The current fourth industrial revolution, or 'Industry 4.0' (I4.0), is driven by digital data, connectivity, and cyber systems, and it has the potential to create impressive/new business opportunities. With the arrival of I4.0, the scenario of various intelligent systems interacting reliably and securely with each other becomes a reality which technical systems need to address. One major aspect of I4.0 is to adopt a coherent approach for the semantic communication in between multiple intelligent systems, which include human and artificial (software or hardware) agents. For this purpose, ontologies can provide the solution by formalizing the smart manufacturing knowledge in an interoperable way. Hence, this paper presents the few existing ontologies for I4.0, along with the current state of the standardization effort in the factory 4.0 domain and examples of real-world scenarios for I4.0.

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Section: Industry 40 Ontological Frameworkmentioning

confidence: 99%

Ontologies for Industry 4.0

Ragavan

Khamis

Fiorini³

et al. 2019

The Knowledge Engineering Review

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“…Besides inference and reasoning, ontologies and RDF enable mapping, which means finding matches or correspondences between concepts in different data structures (Staab and Studer, 2009). In the context of mechatronic products, ALLIGATOR is an approach for mapping mechanical and electronic viewpoints of the same product (Grangel-Gonzalez et al, 2016). Therefore, the approach uses an RDF scheme for identifying conflicts in between AutomationML documents, which are an Industry 4.0 standard for exchanging plant engineering information.…”

Section: Semantic Models In Engineering Designmentioning

confidence: 99%

Integrating the Mechanical Domain into Seed Approach

Dworschak¹,

Kügler²,

Schleich³

et al. 2019

Proc. Int. Conf. Eng. Des.

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Data-driven technologies have found their way into all areas of engineering. In product development they can accelerate the customization to individualized requirements. Therefore, they need a database that exceeds common product data management systems. The creation of this database proves to be challenging because in addition to explicit standards and regulations the product design contains implicit knowledge of product developers. Hence, this paper presents an approach for the semantic integration of the engineering design (SeED). The goal is an automated design of an ontology, which represents the product design in detail.SeED fulfils two tasks. First, the ontology provides a machine-processable representation of the products design, which enables all kind of data-driven technologies. Among other representations, the ontology contains formal logics and semantics. Accordingly, it is a more comprehensible solution for product developers and knowledge engineers. Second, the detailed representation enables discovering of intrinsic knowledge, e.g. design patterns in product generations. Consequently, SeED is a novel approach for efficient semantic integration of the product design.

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“…In Industry 4.0, semantic interoperability is multi-faceted due to the different types of assets and standards and vocabularies to describe them. González et al [35], [36] propose to employ the Resource Description Framework (RDF) as "the lingua franca to represent and integrate information in Industry 4.0 contexts", as a "middle layer" within AdminShells to support interoperability. The approach can manage specifications in English and German.…”

Section: Related Workmentioning

confidence: 99%

Towards a Methodology for RAMI4.0 Service Design

Buenabad-Chávez

Kecskeméti

Tountopoulos³

et al. 2018

2018 Sixth International Conference on Enterprise Systems (ES)

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The Reference Architecture Model Industry 4.0 (RAMI4.0) proposes two models to guide the design of virtual representations of assets. A cubic model represents assets in the form of layers and allows them to be tracked over their lifetime and assigned to technical or organizational hierarchies. The I4.0 component model suggests how to organise virtual representations, i.e., asset properties (data and functions). A service hierarchy has also been proposed as the mechanism to gain access to asset properties. This paper presents an analysis of the RAMI4.0 service hierarchy, compared to traditional service oriented architecture, towards a methodology for the design of RAMI4.0 services. We envision a methodology based on objectoriented analysis and design principles. The rationale behind our approach is the similarity that holds between objects and assets as I4.0 components. Data and functions within objects are accessible through method invocations; data and functions of assets are accessible through service invocations. The paper outlines the use of this approach in defining RAMI4.0 services for a software system being designed to support decision making under events that disrupt manufacturing operations.

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An RDF-based approach for implementing industry 4.0 components with Administration Shells

Cited by 40 publications

References 15 publications

Ontologies for Industry 4.0

Ontologies for Industry 4.0

Integrating the Mechanical Domain into Seed Approach

Towards a Methodology for RAMI4.0 Service Design

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