Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.794590
Title: The manufacturing domain ontology for simplifying interoperability of systems for contact lens manufacture
Author: Atkinson, Hayden
ISNI:       0000 0004 8500 2928
Awarding Body: Brunel University London
Current Institution: Brunel University
Date of Award: 2018
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Abstract:
The advances in manufacturing systems and automation in recent years has been vast. The mechatronic age is apparent in any highly automated manufacturing facility. There is however, an emerging need to improve the domain model to keep pace. Much has been written regarding "big data" and the interoperability of systems, the detrimental effects of dirty data. This research sets out to review the current state of manufacturing domain data, the options for manipulating data while an organisation grows through natural growth and acquisitions. The research adopted a design science methodology to guide through an iterative process, adding more data and creating a higher level of understanding through each cycle. This research follows using a 4D foundation ontology to model the products and processes of a test case manufacturing organisation creating a minimum viable ontology. The accomplishments of this thesis are designing, building a foundation grounded ontological domain model for contact lenses and contact lens manufacturing process. In the final cycles of the evaluation, to empirically demonstrate the use of a philosophical foundational ontology within a legacy data conversion process enhancing the interoperability of systems by identifying and cleaning erroneous data. This research demonstrates the use of data representation, modelling using space time maps to explain both simple and complex domain data interactions within products and manufacturing processes.
Supervisor: Kamal, M. ; De Cesare, S. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.794590  DOI: Not available
Keywords: Conceptual modelling ; Paper data ; Multi-faceted data
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