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:
CreatorsEmail
Conte, Salvatoresalvatore.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:
nomeemail
D'Anna, Andreaandrea.danna@unina.it
Tutor:
nomeemail
D'Addona, Doriana MarilenaUNSPECIFIED
Teti, RobertoUNSPECIFIED
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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