Minimisation of energy consumption variance for multi-process manufacturing lines through genetic algorithm manipulation of production schedule
- Submitting institution
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University of Central Lancashire
- Unit of assessment
- 12 - Engineering
- Output identifier
- 13153
- Type
- D - Journal article
- DOI
-
-
- Title of journal
- Engineering Letters
- Article number
- -
- First page
- 40
- Volume
- 23
- Issue
- 1
- ISSN
- 1816-093X
- Open access status
- Out of scope for open access requirements
- Month of publication
- February
- 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
-
3
- Research group(s)
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B - Centre for Advanced Digital Manufacturing Technology
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This research was funded by EPSRC and BAE Systems Military Air and Information through an to develop digital manufacturing capabilities for aerospace platforms. (Industrial CASE studentship award, Voucher 11220144, £94,621). The paper reports a manufacturing scheduling optimisation algorithm that was developed based on genetic searching to minimise energy consumption variation. It demonstrated a significantly high reduction of 70% energy variation (on average) for multi-process production lines. The paper was invited as a follow-on publication from research which received the award of best paper at the International Conference on Intelligent Automation and Robotics, San Francisco, 2014.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
