Ontology‐based context‐sensitive computing for FMS optimization

Abstract

2014),"Maximizing agreement on diverse ontologies with "wisdom of crowds" relation classification", Online Information Review, Vol. 38 Iss 5 pp. 616-633 http://dx.If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -The purpose of this paper is to present an ontology-based approach of context-sensitive computing for the optimization of flexible manufacturing systems (FMS). Design/methodology/approach -A context-sensitive computing approach is presented, integrated on top of FMS control platform. The approach addresses how to extract manufacturing contexts at source, how to process contextual entities by developing an ontology-based context model and how to utilize this approach for real time decision making to optimize the key performance indicators (KPIs). A framework for such an optimization support system is proposed. A practical FMS use case within SOA-based control architecture is considered as an illustrative example and the implementation of the core functionalities to the use case is reported. Findings -Continuous improvement of the factory can be enhanced utilizing context-sensitive support applications, which provides an intelligent interface for knowledge acquisition and elicitation. This can be used for improved data analysis and diagnostics, real time feedback control and support for optimization.Research limitations/implications -The performance of context-sensitive computing increases with the extraction, modeling and reasoning of as much contexts as possible. However, more computational resources and processing times are associated to this. Hence, the trade-off should be in between the extent of context processing and the required outcome of the support applications. Practical implications -This paper includes the practical implications of context-sensitive applications development in manufacturing, especially in the dynamic operating environment of FMS. Originality/value -Reported results provide a modular approach of context-sensitive computing and a practical use case implementation to achieve context awareness in FMS. The results are seen extendable to other manufacturing domains.

Holistic Context-Sensitivity for Run-Time Optimization of Flexible Manufacturing Systems

“…As context integrates different knowledge sources and binds knowledge to the user to guarantee that the understanding is consistent, context modeling is extensively investigated within Knowledge Management research [8]. According to [9], context-sensitive computing uses contexts to provide relevant information and/or services to the users or applications. The relevancy depends mainly on the tasks or on the application domain [10].…”