Journal article 1355 views
A coupled penalty matrix approach and principal component based co-linearity index technique to discover product specific foundry process knowledge from in-process data in order to reduce defects
R.S Ransing,
C Giannetti,
M.R Ransing,
M.W James,
Rajesh Ransing 
,
Cinzia Giannetti
,
Cinzia Giannetti
Computers in Industry, Volume: 64, Issue: 5, Pages: 514 - 523
Swansea University Authors:
Rajesh Ransing , Cinzia Giannetti
Full text not available from this repository: check for access using links below.
DOI (Published version): 10.1016/j.compind.2013.02.009
Abstract
A coupled penalty matrix approach and principal component based co-linearity index technique to discover product specific foundry process knowledge from in-process data in order to reduce defects
| Published in: | Computers in Industry |
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| ISSN: | 0166-3615 |
| Published: |
2013
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa14574 |
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| Item Description: |
Traditional techniques are unable to discover correlations among factors in the ‘noisy’ in-process data. The proposed technique of discovering correlations in the reduced space defined by the principal components is shown to be a novel and robust method. It allows process engineers to view limited number of important penalty matrices from the thousands of possible combinations. The approach has been embedded training courses offered by the American Foundrymen and Institute of Cast Metal Engineers in UK. Elsevier publishers have chosen to make this paper open source, for a period of three months, for the benefit foundry engineers around the world. |
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| College: |
Faculty of Science and Engineering |
| Issue: |
5 |
| Start Page: |
514 |
| End Page: |
523 |