Machine tool capability profiles for representing machine tool health
- Submitting institution
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University of the West of Scotland
- Unit of assessment
- 12 - Engineering
- Output identifier
- 10707701
- Type
- D - Journal article
- DOI
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10.1016/j.rcim.2014.11.002
- Title of journal
- Robotics and Computer-Integrated Manufacturing
- Article number
- -
- First page
- 70
- Volume
- 34
- Issue
- -
- ISSN
- 0736-5845
- Open access status
- Out of scope for open access requirements
- Month of publication
- August
- Year of publication
- 2015
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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5
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The paper presented new mechanisms for predicting machine tool health and accuracy during manufacturing operations which are vital to successful processing. While many standards exist associated with machine tool accuracy there was little published methodologies associated with machine tool health and in particular, the ability to exchange data between the various systems available to allow assessment of machine tool capability. This work presented a novel approach for representing statistical machine tool accuracy information while maintaining the compliancy within prevalent machine tool testing standards. The work was a collaborative venture with University of Bath.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -