Manufacturing companies must have a good knowledge of their products and processes to be competitive. This is increasingly important as products become more complex. There are many recent developments in product representation, but these do not currently address manufacturing process issues, or integrate with techniques such as key characteristics and Variation Risk Management. This paper describes the development of a database which models complex product specifications, down to component feature detail. It allows the representation of manufacturing operations, process chains and costs, and maps these models. Key product characteristics are flowed down to the detailed feature level, and the associated variability and capability assessed. The paper commences by outlining some of the recent significant developments in product representation. The database structure and associated applications are described. Finally, an example is provided for the use of the database, based on the representation of gas turbine engine from a major aerospace manufacturing company.
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1 October 2004
Research Article|
October 01 2004
Knowledge management for manufacturing: the product and process database
Oluwatuminu Balogun;
Oluwatuminu Balogun
Research Associate, at the School of Mechanical, Materials, Manufacturing Engineering and Management, University of Nottingham, Nottingham, UK
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Hisham Hawisa;
Hisham Hawisa
Researcher at the School of Mechanical, Materials, Manufacturing Engineering and Management, University of Nottingham, Nottingham, UK
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James Tannock
James Tannock
Senior Lecturer, at the School of Mechanical, Materials, Manufacturing Engineering and Management, University of Nottingham, Nottingham, UK
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Publisher: Emerald Publishing
Online ISSN: 1758-7786
Print ISSN: 1741-038X
© Emerald Group Publishing Limited
2004
Journal of Manufacturing Technology Management (2004) 15 (7): 575–584.
Citation
Balogun O, Hawisa H, Tannock J (2004), "Knowledge management for manufacturing: the product and process database". Journal of Manufacturing Technology Management, Vol. 15 No. 7 pp. 575–584, doi: https://doi.org/10.1108/17410380410555826
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