| Machining-induced residual stresses (RS) are one of the most important currently discussed topics in metal cutting, as they play a crucial role in controlling the performance of a machined part, and in deciding whether or not it meets the required specifications, especially in the automotive and aerospace industries. RS may result in unacceptable deformations that may prevent the part from meeting the required tolerances. They also affect the static and fatigue strengths of the component, its magnetic and electrical properties, and its corrosion resistance.;In this thesis, PEA has been used to understand different important RS phenomena, and a special attention has been given to modify the currently available FE approach to predict RS, in order to overcome its long computational time. The thesis mainly focuses on three important topics, which are: (1) understanding the role of different workpiece material properties in controlling the induced RS, (2) developing two FE approaches that overcome the long computational time of RS prediction, and (3) understanding the effects of different cutting parameters on RS.;First, the orthogonal cutting process was modelled using the ALE technique, as it is more advantageous over the traditional Lagrangian and Eulerian techniques. This was done using the commercial FE software ABAQUS/Explicit(TM). After that, RS were predicted using three different FE approaches, which are referred to as approaches A, B, and C. Approach A is the only currently available approach to predict machining-induced RS, and is referred to in the thesis as the traditional approach. The commercial FE software ABAQUS/Explicit(TM) was used in this approach. Although approach A suffers from having very long computational time, it does not introduce any new sources of modelling errors while predicting RS. This is why approach A was used to predict the RS profiles that were used for validating the current FE work, by comparing them to experimental profiles obtained using the same cutting conditions. The X-ray diffraction method along with electrochemical etching was used for measuring RS experimentally. Approaches B and C are FE approaches that have been developed in the course of this thesis, in order to overcome the long computational time of RS prediction when using the traditional approach. The commercial FE software ABAQUS/Explicit(TM) and ABAQUS/Implicit(TM) were used in approach B, while a FE program has been written by the author for RS prediction in approach C. The two developed approaches have been proved to be valid, with acceptable deviation from the traditional one, and succeeded in cutting down the computational time of RS prediction from the order of days (approach A) to few minutes (approach B) and few seconds (approach C).;The effects of different workpiece material properties on RS were studied and understood, which represents an important contribution of the current work. This mainly helps predicting how different workpiece materials will behave relative to each other, when being cut using the same cutting conditions. The studied properties were divided into two categories; mechanical and thermal properties. The mechanical properties included the initial yield strength (A), strain hardening coefficient (B), and strain hardening exponent (n), while the thermal properties included the thermal conductivity (k) and thermal softening exponent (m). In general, surface tensile RS were found to increase in materials with higher B, n, k, and m values, and lower A values. The thickness of the tensile layer was almost unaffected by any of the studied properties except k, where materials with higher k values experienced significantly thicker tensile layers. All the presented results were explained in terms of material plastic deformation and heat generation and dispersion within the workpiece.;For a long period of time, experimental investigation played the main role in studying different RS phenomena. After that, finite element analysis (FEA) started to have a significant role in understanding the process of metal cutting including RS; however, experimental validation is still mandatory. PEA has been used in studying: (1) the effects of different cutting parameters on RS; (2) different sources of RS and the interaction between them; and (3) how RS affect part performance. However, the long computational time of RS prediction has been always an issue. Due to the drawbacks in the traditional Lagrangian and Eulerian PE techniques, the arbitrary-Lagrangian-Eulerian (ALE) technique has been introduced in modelling the cutting process in the late 1990s. This was mainly because ALE combines the advantages of the two traditional techniques, and avoids their main drawbacks.;The effects of three different cutting parameters, namely the tool-edge radius (R), feed rate (f), and cutting speed (V), on RS were also examined. R had the most significant effect on the magnitude of RS in the near-surface layer. Using tools with larger R induced higher surface tensile RS, as it resulted in more plastic deformation and higher temperatures across the workpiece thickness. A stable stagnation (dead-metal) zone was developed and its size increased with R; this zone helped explaining the effects of R on material plastic deformation, which consequently explained its effects on RS. Since the effect of V on RS is mainly attributed to its thermal effects, its effect on the magnitude of RS was found to vary significantly based on workpiece material properties, especially k. In general, V had a slight effect on the RS distribution; however, its effect became more significant in materials with higher k. Finally, f was found to have a very limited effect on the distribution of RS. |
