Conte, Salvatore (2021) Smart process monitoring of machining operations. [Tesi di dottorato]
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| Item Type: | Tesi di dottorato |
|---|---|
| Title: | Smart process monitoring of machining operations |
| Creators: | Creators Email Conte, Salvatore salvatore.conte@unina.it |
| Date: | 15 April 2021 |
| Number of Pages: | 106 |
| Institution: | Università degli Studi di Napoli Federico II |
| Department: | Ingegneria Chimica, dei Materiali e della Produzione Industriale |
| Dottorato: | Ingegneria dei Prodotti e dei Processi Industriali |
| Ciclo di dottorato: | 33 |
| Coordinatore del Corso di dottorato: | nome email D'Anna, Andrea andrea.danna@unina.it |
| Tutor: | nome email D'Addona, Doriana Marilena UNSPECIFIED Teti, Roberto UNSPECIFIED |
| Date: | 15 April 2021 |
| Number of Pages: | 106 |
| Keywords: | sensor monitoring; artificial intelligence; manufacturing; cutting; grinding; artificial neural network; bees algorithm; industry 4.0 |
| Settori scientifico-disciplinari del MIUR: | Area 09 - Ingegneria industriale e dell'informazione > ING-IND/16 - Tecnologie e sistemi di lavorazione |
| Date Deposited: | 05 Dec 2022 13:18 |
| Last Modified: | 05 Dec 2022 16:28 |
| URI: | http://www.fedoa.unina.it/id/eprint/13463 |
Collection description
The following thesis explores the possibilities to applying artificial intelligence techniques in the field of sensory monitoring in the manufacturing sector. There are several case studies considered in the research activity. The first case studies see the implementation of supervised and unsupervised neural networks to monitoring the condition of a grinding wheel. The monitoring systems have acoustic emission sensors and a piezoelectric sensor capable to measuring electromechanical impedance. The other case study is the use of the bees' algorithm to determine the wear of a tool during the cutting operations of a steel cylinder. A script permits this operation. The script converts the images into a numerical matrix and allows the bees to correctly detect tool wear.
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