Core manufacturing ontology to model manufacturing operations and sequencing knowledge

Sattam Saha, W.D. Li, Z. Usman, Nazaraf Shah

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
38 Downloads (Pure)

Abstract

It is critical to capture and share product manufacturability knowledge along with manufacturing operations and their sequences to enhance the competitiveness of manufacturing enterprises. The developed approaches have proven to be expensive and time-consuming. In this paper, a new core manufacturing ontology is developed to model manufacturing operations, sequence knowledge and make it easily shareable. The ontological approach involves the identification and definition of a core set of concepts with relations to develop the hierarchical structures of manufacturing models. The ontological model is then formalised through the Web Ontology Language, while formal axioms and rules are written in the Semantic Web Rule Language. The model was validated in an industrial environment via collaboration with one of the largest aero engine manufacturing companies. The generic nature of the proposed model renders that it is capable of capturing manufacturing operations and their sequences into proper categorisation. The multifaceted capability of the ontological model can greatly facilitate manufacturing engineers in decision-making for new product manufacturing planning.
Original languageEnglish
Pages (from-to)5-23
Number of pages19
JournalService Oriented Computing and Applications
Volume17
Early online date23 Jan 2023
DOIs
Publication statusPublished - Mar 2023

Bibliographical note

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This document is the author’s post-print version, incorporating any revisions agreed during the peer-review process. Some differences between the published version and this version may remain and you are advised to consult the published version if you wish to cite from it.

Funder

This research is sponsored by the AME studentship from Coventry University and Institute of Advanced Manufacturing and Engineering. The authors also acknowledge the support from Rolls Royce Plc for research validation.

Keywords

  • Ontology
  • Manufacturing operations
  • Operation sequences
  • Manufacturing operation knowledge
  • Knowledge sharing

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