Rule-based operator decision support for grinding circuit control
| dc.contributor.author | Olivier, Jacques | |
| dc.contributor.supervisor | Chris Aldrich | en_US |
| dc.contributor.supervisor | Wan-Quan Liu | en_US |
| dc.date.accessioned | 2021-10-26T01:27:41Z | |
| dc.date.available | 2021-10-26T01:27:41Z | |
| dc.date.issued | 2021 | en_US |
| dc.identifier.uri | http://hdl.handle.net/20.500.11937/86213 | |
| dc.description.abstract |
This work investigated the application of interpretable machine learning methods for process control in the mineral processing industry. The thesis presents a methodology to extract intelligible rules from grinding circuit data using decision tree algorithms. The rule sets can aid process operators tasked with supervisory control of grinding circuits. | en_US |
| dc.publisher | Curtin University | en_US |
| dc.title | Rule-based operator decision support for grinding circuit control | en_US |
| dc.type | Thesis | en_US |
| dcterms.educationLevel | MPhil | en_US |
| curtin.department | WASM: Minerals, Energy and Chemical Engineering | en_US |
| curtin.accessStatus | Open access | en_US |
| curtin.faculty | Science and Engineering | en_US |
| curtin.contributor.orcid | Olivier, Jacques [0000-0002-4837-2175] | en_US |