Depending on the material system and machining conditions, the localized strain, strain rate and temperature fields induced to the material during the machining process can be intense. Therefore, a wide variety of microstructural evolutions are likely to occur below the machined surface. These microstructural changes take place at various scales. First of all, due to the severe plastic deformation below the machined surface, the crystallographic orientation of grains can change dramatically. In addition, if the levels of the induced temperature and strain are high enough, recrystallization may occur, new grains may form and subsequently grow. Additionally, contingent upon the duration of the machining process, partial grain growth might also happen. Last but not least, if the material is consisted of more than one phase, the microstructural characteristics of secondary phases will also evolve. The ultimate result of all the aforementioned evolutions produces remarkable changes in the mechanical and thermal (and almost all other) properties of the material, which consequently affect the response of the material during service. A comprehensive modeling framework that reliably captures all the aspects of the above microstructural evolutions in machining is absent in the open literature. This work coalesces concrete and all-inclusive modeling toolsets into a unified scheme to follow the mentioned phenomena in machining of aluminum alloy 7075. The modeling outcomes are verified by experimental results to assure reliability. Finite element analyses were applied to obtain the stress, temperature, strain and strain rate fields developed in the material during machining at different parameters. Kinetic-based models were exploited to determine the possible recrystallization or grain growth. A viscoplastic self-consistent crystal plasticity model was utilized to investigate texture evolution below the machined surface. Also for multi-phase materials, the first steps in developing a totally new constitutive model to yield the extent of the possible refinement in the second phase precipitates, were taken. The main goal of the work was to link the above-mentioned microstructural evolutions to process parameters of machining by mathematical derivation of process path functions. Therefore, prediction of microstructural changes as a result of changing the process parameters became possible; which has significant industrial potential and importance. Additionally, such a direct and complete linkage between machining and microstructure is completely new to the scientific community in manufacturing and design fields.

Abrasive Flow Machining, (AFM), is a non-traditional machining process that is achieved by extruding polyborosiloxane, (a viscoelastic polymer), containing abrasive grit additions, across surfaces, edges, and through component cavities. The AFM process is a complex one and its machining mechanism is still only partially understood since previous research into the process has mainly been limited to qualitative study. The present work undertook to investigate the relationship between the rheological characteristics of polyborosiloxane/grit mixtures and the associated machining parameters. A significant increase in the quantitative data available with respect to both the rheological and machining characteristics of these mixtures has been provided as a consequence of the investigations. Experiments were conducted using low viscosity, (LV), medium viscosity, (MV), and high viscosity, (HV), polyborosiloxane base media, in conjunction with silicon carbide abrasive grit of 60 and 100 Mesh size; the ratios of grit to base polymer utilised in the experiments were 0,1, and 2. The test pieces used in the experimental work were mild steel dies having a diameter of 15mm and a length of 1 5mm, and the equipment used to conduct the experiments was an Extrude Hone mark 7A machine. The investigations conducted have revealed that for all polymer/grit mixtures an increase in the number of extrusion cycles results in an increase in the stock removed, an improvement in the surface roughness, and an increase in the temperature of the mixture. Furthermore as the usage of the medium increases the grit particle wear increases so that there is a corresponding decrease in the machining parameters. For all mixtures there appears to be no correlation between the viscosities of the base media types and the machining parameters. However, a relationship is demonstrated between the machining parameters and variations in the viscosities of the grit/polymer mixtures based on a specific polymer base. The factors that appear to influence this relationship are the grit to polymer ratio, the grit size, and the temperature. The most important of these parameters are suggested to be the grit to polymer ratio and temperature since these variables appear to affect the viscosity behaviour and the associated machining parameters. In addition the investigations showed that the viscosities and associated rheological dependent parameters correspond to the qualitative viscosity nomenclature given to the different media types by the manufacturer. A shear history effect is also exhibited in each of the polymer types.

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Sculptured parts, characterized by interconnected and bounded parametric surface patches, are widely used in aerospace, automobile, shipbuilding and plastic mold industries due to their functional and aesthetic properties. However, adoption of these sculptured surfaces on mechanical products increases the complexity of manufacturing and puts forward a challenge to achieve high machining quality and productivity, as well as low machining cost. Machining of sculptured parts is mostly carried out on a milling machine. The milling process can be divided into: rough cut (roughing) and fine cut (finishing) operations. Rough machining is used to remove excess stock material, while finish machining is aimed at generating adequate tool paths for producing the final shape of the part. When a sculptured part is machined from prismatic stock, a large amount of rough cut, up to 90 percent of the total machining, is required. Cutting time reduction in rough machining can considerably improve the efficiency of sculptured part machining, lower production cost. This research focuses on the productivity improvement of sculptured part rough milling machining that is affected essentially by CNC tool path and machining parameters. Two major strategies, machining path strategy and machining parameter strategy are investigated. A number of new methods are introduced to generate highly productive CNC tool path and machining parameters. Study on machining path strategy involves approaches of generating 2½D CNC tool path trajectory, creating new tool path patterns, and automatically identifying optimal tool path pattern. While research on machining parameter strategy focuses on the minimization of cutting time, based upon the changing part geometry during machining and manufacturing constraints. A method that incorporates an existing milling process model into the cutting parameter optimization to predict instantaneous cutting force and identify the most effective cutting parameters is introduced. An improved model cofficient determination scheme using numerical optimization and artificial neural network techniques is developed, and extensive cutting tests are carried to allow the milling process model to fit into the cutting parameter optimization. A method for the automated formulation and solution of the cutting time minimization problem is also introduced to allow important machining parameters, including the number of cutting layers, depth of cut, feed rate and cross-cutting depth, to be determined without human intervention. The research directly contributes to automated sculptured part machining, and has a great potential to produce significant economical benefits to manufacturing industry. The study also establishes a platform for further research and development on intelligent sculptured part machining. / Graduate

Because of the exceptional physical, chemical, electric and mechanical properties of hard and brittle materials, such as ceramics, glass and diamond film etc, those are considerably valued in high technology industry. Although those materials can be machined using the ECDM method, its machining mechanism is still indeterminate. In this study, a static electrical pitting tester is employed, the electrolyte is KOH(eq), the workpiece is glass, and we change the parameters, such as supply voltage, supply current and machining gap to investigate the mechanism of static Electrochemical Discharge Machining. From the experimental results, which are SEM pictures of machined glass and variations of current, we can clearly infer the mechanism of static-ECDM. Moreover, the most important reason for damaging glass is supply voltage. Even increasing supply voltage can make glass cleave. And the main factor to make the loop become insulating is supply current. While the supply voltage is 50V, the supply current is 8A, and in different machining gap condition, the results show that it has a certainly gap to discharge during the machining process, and the particular gap is about 49£gm. The results also show that the machining model has two kinds of types. When the machining gap is shorter than 49£gm, the machining model is from ring to circle; contrarily, when it is longer than 49£gm, the machining model is circle directly.

<p> </p><p>The increasing demands for precision and efficiency in machining call for new control strategies for machining systems based on the identification of static and dynamic characteristics under operational conditions. By considering the machining system as a closed-loop system consisting of a machine tool structure and a machining process, the join system characteristics can be analyzed. The capability of a machining system is mainly determined by its static and dynamic stiffness.</p><p>The goal of this thesis is to introduce some concepts and methods regarding the identification of machining system stability. Two methods are discussed, one for the static behaviour analysis of a machine tool, and one for dynamic stability of a machining system. Preliminary results are indicating unambiguous identification of capabilities of machining systems static and dynamic characteristics.</p><p>The static behaviour of a machine tool is evaluated by use of a loaded double ball bar (LDBB) device. The device reproduces the real interaction between the join system, the machine tool elastic structure and the cutting process. This load is not equivalent to real cutting forces, but it does have a similar effect on the structure. This has been investigated both trough simulation and experimental work.</p><p>It is possible to capture the process – ­machine interaction in a machining system by use of the model-based identification approach. The identification approach takes into consideration this interaction and can therefore be used to characterize the machining system under operational conditions. The approach provides realistic prerequisites for in-process machining system testing. The model parameters can be further employed for control and optimization of the cutting process. Using different classification schemes, the model-based identification method is promising for the detection of instability.</p><p>Furthermore, it is the author’s belief that a model-based stability analysis approach is needed to exploit the full potential of a model driven parts manufacturing approach.</p>

Many high value-machining processes such as milling and drilling have been performed by expensive and dedicated (single purpose) machine tools including CNC machine tools. Industrial robots are a good alternative to these conventional dedicated machine tools due to the robots’ many advantages such as lower cost, larger workspace, higher flexibility of motion, and versatility. Despite these advantages, several barriers prevent them from being widely adopted for high value machining purposes. Two of these barriers are low and nonlinear stiffness of the industrial robot arm and the manufacturing end-users not knowing the capabilities and advantages of robots in machining applications. This research sets out to help a typical machining operator who is not an expert in robotics to learn the capability of a given robotic machining system. This study should help the operator plan robotic machining processes by presenting process models and visual maps for a variety of machining processes and workpiece materials. The study shows in particular how the cutting force and the compliance of a robotic machining system affect machining processes. To meet this objective, we present a framework for planning development for any given robotic machining application domain. First, we select primary performance parameters (including joint torque limit and end-effector positional error) and control parameters (including machining parameters, end-effector position, and workpiece position) for robotic machining. Then, we present the system models and visual performance maps for the functional parameters of robotic machining processes. The focus is on cutting forces for the ten selected machining processes and end-effector positional error of a robotic machining system due to the compliance of a robotic system (i.e., robot manipulator and cutting tool) and joint error (due to sensor error and gear backlash). Finally, we present five applications to show how to use visual maps for preliminary planning scnearios of robotic machining processes. The applications present a step-by-step process for selecting from cutting parameters to workpiece position parameters by utilizing performance requirements and visual maps developed in this research. / text

Rapid prototyping (RP) is a supplementary additive manufacturing method to the traditional Computer Numerical Controlled (CNC) machining. The selection of the manufacturing method between RP and CNC machining is currently based on qualitative analysis and engineers’ experience. There are situations when parts can be produced using either of the methods. In such cases, cost will be the decisive factor. However, lack of a quantitative cost estimation method to guide the selection between RP and CNC machining makes the decision process difficult. This thesis proposes an automated cost estimator for CNC machining and Rapid Prototyping. Vertical CNC milling and Stereolithography Apparatus (SLA) RP technology are selected in specific, for cost modeling and process comparison. A binary questionnaire is designed to help estimate the CNC setup cost. An SLA build time estimator is implemented based on 3D systems’ SLA3500 machine. SLA post processing cost is also investigated. Based on the developed methods, a prototype software tool was created with an output to Excel chart to facilitate the selection. Five cases have been studied with the software and the predicted results are found reasonable and effective.

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