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A knowledge-based approach for the selection of assembly equipment based on fuel cell component characteristics

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review


Original languageEnglish
Title of host publicationIECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society
Number of pages6
Publication statusPublished - 1 Nov 2015
Publication typeA4 Article in a conference publication
EventAnnual Conference of the IEEE Industrial Electronics Society -
Duration: 1 Jan 1900 → …

Publication series

ISSN (Print)1553-572X


ConferenceAnnual Conference of the IEEE Industrial Electronics Society
Period1/01/00 → …


Unpredictable and dynamic markets are driven by an ever more informed customer base and rapid technological evolution. In order stay competitive, organisations producing physical products need to be agile. To realise a product, an organisation must go through several phases including product design, process planning and manufacturing system design. These phases can exist within and across organisations, spanning the globe and utilizing an enormous range of information and communication standards. So as to understand the requirements of the predominantly sequential phases, resources are exhausted in converting information into a language which upstream and downstream phases can understand. This research paper aims to reduce this effort by capturing knowledge in a core ontology which is formed by product, process and resource domain ontologies. The vision is that phase or domain experts input information into this ontology, which then infers requirements for the adjacent phases based on predefined relationships. The presented approach permits the insertion of additional information as it becomes available because ontologies are extensible and scalable. This supports a concurrent engineering approach and accommodates the needs of modern businesses. This research paper presents a proof of concept based on a Proton Exchange Membrane Fuel Cell (PEMFC). The rationale for the choice of classes and properties in the model are described. The model is successfully proved by describing liaison precedence and the selection of appropriate assembly equipment.


  • assembling, Assembly, assembly equipment selection, communication standard, Fuel cells, knowledge-based approach, knowledge based systems, manufacturing system design, Manufacturing systems, ontologies, ontologies (artificial intelligence), ontology, PEMFC, power engineering computing, PPR, process planning, product design, proton exchange membrane fuel cell, Proton Exchange Membrane Fuel Cell (PEMFC), proton exchange membrane fuel cells, reasoning, Resource description framework, resource domain ontology, Semantics

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