2018
DOI: 10.1007/s10845-018-1427-6
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The development of an ontology for describing the capabilities of manufacturing resources

Abstract: Today's highly volatile production environments call for adaptive and rapidly responding production systems that can adjust to the required changes in processing functions, production capacity and dispatching of orders. There is a desire to support such system adaptation and reconfiguration with computer-aided decision support systems. In order to bring automation to reconfiguration decision making in a multi-vendor resource environment, a common formal resource model, representing the functionalities and cons… Show more

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Cited by 115 publications
(35 citation statements)
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“…Information processing often influences the decision-making of the firm [91]. Decision-making itself is critical as numerous decisions which influence the firm's performance (such as the production, process, or service dimensions of the firm) need to be made [92]. Hence, gathering more information enables firms to arrive to better decisions [93].…”
Section: Resource-based Viewmentioning
confidence: 99%
“…Information processing often influences the decision-making of the firm [91]. Decision-making itself is critical as numerous decisions which influence the firm's performance (such as the production, process, or service dimensions of the firm) need to be made [92]. Hence, gathering more information enables firms to arrive to better decisions [93].…”
Section: Resource-based Viewmentioning
confidence: 99%
“…Some of these ontologies focus on a narrow field, such as manufacturing resource planning, and they do not formalize predictive maintenance-related concepts, e.g., machinery Failure and Fault. Also, none MSDL [21] MRO [22] ONTO-PDM [26] MCCO [27] MaRCO [28] Sensing System Ontology [24] OntoProg Ontology [23] MPMO of the existing ontologies standardize the concepts related to chronicle mining. To jointly use chronicle mining with semantic technologies for a predictive maintenance task, the knowledge-based model should incorporate not only the machine-interpretable knowledge of manufacturing entities such as product and process but also the knowledge about chronicles within which the machinery failures are described in a structured way.…”
Section: Existing Knowledge-based Models To Predictive Maintenancementioning
confidence: 99%
“…As part of the efforts of the EU project ReCaM, an ontologybased approach to capability modeling was developed [22]. It features SPARQL Inference Notation (SPIN) rules for the orchestration of higher-level capabilities in a hierarchical fashion and conducts matchmaking queries based on modeled capabilities.…”
Section: Related Workmentioning
confidence: 99%