Optimization of residual stresses generated by ultrasonic nanocrystalline surface modification through analytical modeling and data-driven prediction

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.

Applications of Intelligent Manufacturing and of Numerical/Analytical Modeling Techniques to Milling Processes

Optimizing the processes required for manufacturing new components and machine parts always constitutes a challenge. The reduction of cost, the increase of process efficiency, the increase of product surface quality, and the properties as well as the design for enhanced life of components are some of the most important goals in industrial practice. Machining, as an important part of manufacturing processes, is still a subject of interest concerning processing of advanced materials and efficient design of individual stages of complex machining processes. Hard machining, as an advanced manufacturing process, is a contemporary subject of research both experimentally and theoretically. In this chapter, it is intended to present the fundamental methods of modeling of hard machining processes with a view to inform the readers of the available knowledge in this field and indicate the most promising aspects of hard machining modeling. After a brief presentation of the characteristics of hard machining processes, numerical and soft computing methods for modeling these processes are presented and discussed, covering the majority of important earlier and contemporary studies on this topic.

Modeling of hard machining

Tungsten heavy alloys (WHAs) with W content 90–95% possess a good combination of high tensile strength as well as high density, thus finding wide applications as counterweights and ballast, radiation shielding, ballistic penetrators, vibration-damped tooling and sporting goods. However, these properties make machining of WHAs to desired dimensions and finish very difficult. A proper understanding of the mechanism of chip formation during machining is surely required that helps in finding the right combination of cutting parameters for achieving higher productivity and better finish. Finite element (FE) simulations help understand the chip formation mechanism with minimum number of experiments. The basic purpose of the current work is to develop an FE model by taking into account three different sets of JC model constants and compare the predicted output variables with experimental machining tests available in the literature.

Effect of Johnson–Cook Material Model Constants on Predicted Chip Morphology and Forces in FE Simulations of Machining Operation for 93% WHA Alloy

Finite element modeling of machining is significantly influenced by various modeling input parameters such as boundary conditions, mesh size and distribution, as well as properties of workpiece and tool materials. The flow stress model of the workpiece material is the most critical input parameter. However, it is very difficult to obtain experimental values under the same conditions as in machining operations.. This paper analyses the influence of different material models for two steels (AISI 1045 and hardened AISI 52100) in finite element modelling of cutting forces. In this study, the machining process is scaled by a constant ratio of the variable depth of cut h and cutting edge radius rβ. The simulation results are compared with experimental measurements. This comparison illustrates some of the capabilities and limitations of FEM modelling.

http://iopscience.iop.org/article/10.1088/1757-899X/142/1/012072/pdf

Elchin Rzayev

Papers

Influence of Material Models Used in Finite Element Modeling on Cutting Forces in Machining