Predictive Maintenance for a Grinding Machine Tool for Bearing Components Manufacturing, Using ANN Method
| dc.contributor.author | Rial, Abdelkader | |
| dc.contributor.author | Mellal, Mohamed Arezki(Promoteur) | |
| dc.date.accessioned | 2022-05-17T11:27:24Z | |
| dc.date.available | 2022-05-17T11:27:24Z | |
| dc.date.issued | 2019 | |
| dc.description | 121 p. : ill. ; 30 cm | en_US |
| dc.description.abstract | The Work consists in developing, testing and validating in a manufacturing company a neural model for predictive maintenance of a grinding machine-tool type that has, during manufacturing process, the highest number of interruptions due to unpredicted maintenance actions. Based on three years maintenance history, a data base will be realized. This data base will be used to generate a neural model of the predictive maintenance. The neural model will be interrogated and, based on the results, the predictive maintenance plan will be drawn up. Applying this neural model and the predictive maintenance plan in the industrial environment could lead to cost reduction | en_US |
| dc.identifier.uri | https://dspace.univ-boumerdes.dz/handle/123456789/8350 | |
| dc.language.iso | en | en_US |
| dc.publisher | Université M'Hamed Bougara Boumerdès: Faculté de Technologie | |
| dc.subject | Predictive maintenance | en_US |
| dc.subject | Maintenance prédictive | en_US |
| dc.subject | Artificial neural networks | en_US |
| dc.subject | Réseau neurone artificiel | en_US |
| dc.title | Predictive Maintenance for a Grinding Machine Tool for Bearing Components Manufacturing, Using ANN Method | en_US |
| dc.type | Thesis | en_US |