Abstract

Milling is one of the most important and common processes widely used in manufacturing industry, which is a very competitive environment. For this reason, manufacturing companies are facing many different challenges. The offering of a variety of high quality products, the restriction of production time and costs, the increase of productivity, and the need for flexibility of production are the goals that manufacturers have to consider and achieve in order to succeed in their field. These aspects relate to the process study, optimization and control, and in recent years many attempts to find possible solutions and techniques to manage these steps in a proper way have been done. The first solution that a lot of enterprises were motivated to research and utilize relates to the application of the finite element modeling (FEM) techniques to study manufacturing processes or to highlight behaviour of products, for example of cutting tools, during the design phase. The second technique deals with the manufacturing process control, and is aimed at the increasing of automation level of modern production systems by evolving them towards the paradigm of Intelligent Manufacturing. The present work is focused on the study and evaluation of the effectiveness of both techniques. The first part of the research presented in this thesis is dedicated to the study of the application of Intelligent Manufacturing Systems to milling processes. In particular, in the Chapter 1 it is discussed the improvement of the artificial operator called Evaluation and Perception Controller (EPC) built by the Mechatronics group of the University of Trento within the national project Michelangelo in 2013. In this thesis it is proposed to improve the performance characteristics of the EPC system in terms of the process quality, described by the surface roughness value. In particular, it is proposed to associate the surface roughness term to the scallop height value, and to include a model that describes the mechanism of scallop height formation into the Optimal Control Problem formulation. Chapter 2 of this work is related to the application of FEM techniques to study milling processes. In particular, in this section the influence of CAD cutting tool models (STEP and STL) on 3D FEM AdvantEdge prediction accuracy in terms of the average and maximum cutting forces, and deformed chip thickness and curvature radius values are studied. In addition, this part of the thesis includes also the discussion of the problems related to the application of 2D FEM modeling techniques to study the influence of cutting tools geometries on the feed and tangential cutting forces that act in three-dimensional cutting processes. Chapter 3 of this thesis is dedicated to the development of a model suitable for prediction of cutting forces that act in non-tilted and tilted side down-milling processes performed with end mills. The development of this model has two purposes. First of all, it can be included into the EPC controller, thus extending the field of the possible applications of this system. The second purpose relates to the fact that in case the side down-milling process simulations are performed by using cutting forces coefficients identified based on 2D FEM cutting forces data, the proposed model allows to overcome the mismatches between real processes and 2D FEM, and to simulate two cutting forces, feed and normal, arising in three-dimensional processes.