Modelli e Tecniche Computazionali Intelligenti per i Processi di Lavorazione

This thesis work aimed at the development of Intelligent Computing Models and Techniques for Manufacturing Processes. In particular, it is focused on: 1. Tool condition monitoring during machining of composite materials. During machining tests of different composite materials, sensor signals obtained from multiple sensors for the measurement of the cutting force and the acquisition of acoustic emission will be detected, digitized and stored. Supervised and unsupervised neural network approaches will be developed for decision making on tool condition. 2. Chip form monitoring during machining. During machining tests on steel alloys, sensor signals obtained from the measurement of the cutting force will be detected, digitized and stored. Two types of supervised neural network approaches will be developed for decision making on chip form recognition: one for single chip form classification and one for favourable/unfavourable chip form identification