This thesis has investigated material removal mechanisms in grinding by considering single grit workpiece interaction. The investigation was performed both experimentally and using finite element simulation. Rubbing, ploughing and cutting mechanisms occurring during the grinding process were studied at the micro scale. Due to its nature the rubbing phase occurs in a very narrow region of grit-workpiece engagement and is difficult to examine under a microscope and so was investigated using FEM simulation. The ploughing mechanism was thoroughly investigated using both experimental tests and FEM simulations, and a similar trend was observed for the pile up ratio along the scratch path from the experimental tests and the FEM simulations. Ploughing and cutting mechanisms in grinding were found to be highly influenced by grit cutting edge shape, sharpness and bluntness. Cutting is the prominent mechanism when the grit cutting edge is sharp, but ploughing is more prominent when the grit cutting edge becomes flattened. In the case of multiple edges scratch formation, ploughing is dramatically increased compared to single edge scratches. Feasibility of ground surface simulation using FEM is demonstrated using multiple pass scratch formation in a cross direction. Although chip formation mechanism is developed at a relatively higher depth of cut (greater than 10 μm), at small scales down to 1 μm, FEM simulation was not a suitable method to use. To reduce the drawbacks of FEM simulation in micro scale cutting, a meshless simulation technique such as smooth particle hydrodynamics is recommended for future studies.

The evolution in precision manufacturing has resulted in the requirement to produce and maintain more accurate machine tools. This new requirement coupled with desire to reduce machine tool downtime places emphasis on the calibration procedure during which the machine's capabilities are assessed. Machine tool downtime can be as much as $120 per hour and is significant for manufacturers because the machine will be unavailable for manufacturing use, therefore wasting the manufacturer's time and potentially increasing lead-times for clients. In addition to machine tool downtime, the uncertainty of measurement, due to the schedule of the calibration plan, has significant implications on tolerance conformance, resulting in an increased possibility of false acceptance and rejection of machined parts. Currently calibrations are planned based on expert knowledge and there are no intelligent tools aiding to produce optimal calibration plans. This thesis describes a method of intelligently constructing calibration plans, optimising to reduce machine tool downtime and the estimated uncertainty of measurement due to the plan schedule. This resulted in the production of a novel, extensible domain model that encodes the decision making capabilities of a subject expert. Encoding the knowledge in PDDL2 requires the discretization of non-linear resources, such as continuous temperature change. Empirical analysis has shown that when this model is used alongside state-of-the-art automated planning tools, it is possible to achieve a reduction in machine tool downtime greater than 10% (12:30 to 11:18) over expert generated plans. In addition, the estimated uncertainty due to the schedule of the plan can be reduced by 59% (48 µm to 20 µm). Further experiments on a PC architecture investigate the trade-o� when optimising calibration plans for both time and the uncertainty of measurement. These experiments demonstrated that it is possible to optimise both metrics reaching a compromise that is on average 5% worse that the best-known solution for each individual metric. Additional experiments using a High Performance Computing architecture show that on average optimality of calibration plans can be improved by 4%; a potential saving of 30 minutes for a single machine and 10 hours for a company with 20 machines tools. This could incur a financial saving in excess of $1200 saving.

Two direct consolidation methods usually used for advanced ceramics have been combined in this project in order to develop a novel fabrication route for traditional ceramics. Specifically the method used is based on the Additive Manufacturing extrusion process using direct writing of high solid loading ceramic pastes and then freeze-casting to solidify the deposited material. This novel fabrication method, for which a patent has been granted, has been christened “Direct Writing Freeze-Casting” (DWFC). Although the DWFC process is the subject of investigation by other researchers for a range of different applications, including the production of medical implants with alumina, the research presented in this thesis focuses on its use in the manufacture of white wares, giftware, and applied arts and crafts in general. This new system will provide designers, potters, artists, craft makers and manufacturers with a flexible and automated way of manufacturing porcelain objects. One of the major challenges to be overcome to exploit the DWFC process is the development of suitable slurry material formulations. Initial trials demonstrated that it is not possible to use conventional clay based porcelain materials with a platelet shaped microstructure which inhibits freeze casting. In this thesis the development and characterisation of non plastic porcelain slurry, based on substitution of kaolin (clay) with a calcined clay material (molochite), which can be processed using this new method is presented. The new non plastic porcelain formulation, which has a high solid load of 75.47% wt., has been subjected to detailed analysis to assess its suitability at each stage of the process; extrusion, freeze-casting (solidification) and firing.

To maximise productivity and reduce scrap in high-value, low-volume production, five-axis machine tool (5A-MT) motion accuracy must be verified quickly and reliably. Numerous metrology instruments have been developed to measure errors arising from geometric imperfections within and between machine tool axes (amongst other sources). One example is the TMBB, which is becoming an increasingly popular instrument to measure both linear and rotary axis errors. This research proposes new TMBB measurement technique to rapidly, accurately and reliably measure all position-independent rotary axis errors in a 5A-MT. In this research two literature reviews have been conducted. The findings informed the subsequent development of a virtual machine tool (VMT). This VMT was used to capture the effects of rotary and linear axis position-independent geometric errors, and apparatus set-up errors on a variety of candidate measurement routines. This new knowledge then informed the design of an experimental methodology to capture specific phenomena that were observed within the VMT on a commercial 5A-MT. Finally, statistical analysis of experimental measurements facilitated a quantification of the repeatability, strengths and limitations of the final testing method concept. The major contribution of this research is the development of a single set-up testing procedure to identify all 5A-MT rotary axis location errors, whilst remaining robust in the presence of set-up and linear axis location errors. Additionally, a novel variance-based sensitivity analysis approach was used to design testing procedures. By considering the effects of extraneous error sources (set-up and linear location) in the design and validation phases, an added robustness was introduced. Furthermore, this research marks the first usage of Monte Carlo uncertainty analysis in conjunction with rotary axis TMBB testing. Experimental evidence has shown that the proposed corrections for set-up and linear axis errors are highly effective and completely indispensable in rotary axis testing of this kind. However, further development of the single set-up method is necessary, as geometric errors cannot always be measured identically at different testing locations. This has highlighted the importance of considering the influences on 5A-MT component errors on testing results, as the machine tool axes cannot necessarily be modelled as straight lines.

Increasing demand for components made of hard and brittle materials such as glasses, steel alloys and advanced ceramics is such that conventional grinding and polishing techniques can no longer meet the requirements of today’s precision manufacturing community. However, it is essential and much needed to undertake such processes based on a scientific approach, i.e. the process to be quantitatively controlled and optimized rather than carried out in a trial-and-error manner. Vibration assisted machining been has demonstrated to reduce the amount of forces, pattern definition on a finished surface. Axial oscillation (parallel to the wheel axis) allows the grains to cut with two more faces. With vibration in two directions, the wheel exposes four times more cutting edges (two edges per oscillation) than in continuous cutting which uses only one edge, which is a great advantage over continuous cutting, Axial oscillation induces an elliptic motion leading to a lapping process, which improves the cutting efficiency as well as the quality of the finished surface. Oscillation greatly reduces the load per grain, reduces wheel wear and induces a chip-breaking effect, which is a great advantage for prevention of wheel loading. In this research, theory modelling and instrumentation for vibration assisted grinding are presented and discussed in depth. The modelling is focused on control of the amplitude of oscillation in the cutting zone which is the fulcrum of this investigation. The control system was developed using Labview 8.5 and Matlab. It was found that the application of vibration reduces the forces, increases the material removal rate and increases the G-Ratio compared to conventional grinding. The superimposition of vibration in axial direction secured better process outcomes in terms of grinding forces (average 25% improvement), surface finish quality and power consumption. In terms of frequencies it was identified that superimposing vibration at 100 Hz in this study provided the lowest forces. In addition, it was shown that at 100 Hz the desired amplitude of oscillation was achieved at the lowest driving voltage, i.e. 4V. Comparing the techniques of control systems, which were open loop, closed loop and conventional grinding, applying vibration always gave better results than with no vibration. The closed loop control in most cases was the best. Comparing oscillating in axial direction and tangential direction, the Axial gave on additional 9% reduction in grinding forces. In general the grinding with vibration assisted secured a greater depth of cut. The oscillating in Axial direction provided an additional 16 % in actual depth of cut, so Applying oscillating in axial direction showed that a significant improvement of quality could be achieved.

Materials which are both lighter and stronger have faced an increased demand over the past decades to fulfil the requirements across a range of industrial applications. More specifically, demands for titanium alloys have increased significantly due to its high strength to weight ratio which is particularly attractive for increasing fuel efficiency in aircrafts and cars and is also used in biomedical implants. Despite the increasing demand for titanium made products, machining titanium alloys remains a significant challenge. High material strength and hardness lead to excessive heat generation at the cutting zone which accumulates and results in high cutting temperatures due to the poor thermal conductivity. The high cutting temperatures together with inherent material properties of titanium are responsible for short tool life and poor surface finish. Despite the environmental and health drawbacks, a generous amount of cutting fluids is commonly used to control the cutting temperature in machining titanium alloys. However, conventional cutting fluids evaporate at high cutting temperatures which isolate the cutting zone by forming a vapour cushion resulting in further increases in cutting temperatures. This research investigates the effects of cryogenic cooling on machinability of Ti-6Al-4V alloy in CNC milling as compared to conventional dry and wet machining environments. Two literature reviews were conducted and a methodology has been developed and implemented consisting of three experimental stages of i) design and manufacture of a cryogenic cooling system, ii) comparative study of cryogenic cooling with dry and wet machining and iii) optimisation of cutting parameters for cryogenic machining. The major contribution of this research can be summarised as design, realisation and assessment of a novel cryogenic cooling system for CNC milling, termed cryogenic shower, which is retrofitable to an existing CNC machining centre. In addition, the research provides a thorough study on the effects of cryogenic cooling on machinability of Ti-6Al-4V alloy in comparison with dry and wet machining. The studies range from power consumption and tool wear through to surface topography and surface integrity. Furthermore, the optimum cutting parameters for cryogenic machining are identified. The research demonstrates that using the cryogenic shower has significantly improved machinability of Ti-6Al-4V through realisation of higher material removal rates, reduced tool wear and improved surface finish, surface topography and surface integrity.

High Efficiency Deep Grinding (HEDG) combines high depths of cut, high grinding wheel speeds with high work piece feed rates to deliver a very high stock removal process that can produce components free of surface damage. High contact temperatures are a characteristic of the process and this produces a mass of hot grinding sparks being ejected from the grinding zone. Neat oil cutting fluids are typically used in HEDG due to their excellent lubricity, but the high grinding wheel speeds employed leads to high levels of highly volatile cutting fluid mist in the machine canopy. This mist can mix with the hot grinding sparks being ejected from the grinding zone to create a potential fire hazard. The project aim was to produce a cutting fluid application strategy for the HEDG regime, focusing on establishing the thermal characteristics of cutting fluids in order to determine the optimum cutting fluid for the HEDG process. The cutting fluid application strategy also involved investigating the optimum means by which to apply the cutting fluid, based on minimising amount of cutting fluid used in the process and in reducing the potential fire hazard. The characteristics that have a thermal impact on the grinding process are the cooling, lubrication, ignition and misting properties of the fluid. A series of tests were established to investigate these properties and therefore allow different fluids to be compared and contrasted for their suitability for the HEDG regime based. Once an optimal cutting fluid had been established, the project then investigated the optimal method of applying this fluid, with particular reference to the type and design of the nozzle used to apply the fluid to the grinding zone. As part of these trials, a series of benchmark tests were also conducted using long established cutting fluid application techniques to enable the benefits of the new strategy to be evaluated. The project concluded that high viscosity neat oil ester based cutting fluids were the best fluids to be used in the HEDG regime due to they excellent lubricity and low misting properties coupled to their relatively high resistance to ignition when compared to neat mineral oils. The studies also found that using a high viscosity ester based fluid and then applying it using a coherent jet nozzle, significant reductions in the grinding powder and specific grinding energy could be achieved whilst significantly lowering the amount of mist in the machine, thus reducing the potential fire hazard and the volume of cutting fluid used by the process.

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The need for high-speed/high-precision machine tools is swiftly increasing in response to the growth of production technology that necessitates high- recision parts and high productivity. The influence of thermally induced errors in machine tools can have a much greater influence on the dimensional tolerances of the final products produced as compared to geometric and cutting force errors. Therefore, to maintain high accuracy of machine tool, it requires an accurate method of thermal error control or compensation using a detailed model. The thermal errors of machine tools are induced by the propagation of heat through the structure of the machine due to excitation of internal and external heat sources such as belt drives, motors and bearings. There has been significant research effort to model thermal errors of machine tools in recent decades. The utilised techniques have proved their capabilities with excellent thermal prediction and compensation results but they often involve significant effort for effective implementation with constraints for complexity, robustness, and cost. One of the most significant drawbacks of modelling machine behaviour using Finite Element Analysis (FEA) is the difficulty of accurately obtaining the characteristic of heat transfer, such as heat power of machine tool heat sources and the various boundary conditions. The aims of this research to provide reliable techniques to obtain heat transfer coefficients of machine tools in order to improve the accuracy of FEA simulations. FEA is used to simulate the thermal characteristics of spindle system of small Vertical Machining Centre (VMC) using SolidWorks Simulation software. Most FEA models of machine tools employ the general prediction technique based on formulae, provided by OEMs, to identify many of the boundary conditions associated with simulating thermal error in machine tools. The formulae method was used to identify the heat transfer coefficients of a small VMC feed drive system. Employing these values allowed FEA to be used to simulate the thermal characteristics of the feed drive model. In addition, an alternative efficient methodology, based on energy balance calculations and thermal imaging, was used to obtain the heat transfer coefficients of the same feed drive system. Then the parameters obtained were applied to the FEA model of the system and validated against experimental results. The residual thermal error was reduced to just 20 % when the energy balance method was employed and compared with a residual of 30 %, when the formulae method was employed. The existing energy balance method was also used to obtain the heat transfer coefficients of the headslide on a small VMC based on thermal imaging data. Then FEA model of the headslide of VMC was created and simulated. There was significant reduction in the thermal error but significant uncertainties in the method were identified suggesting that further improvements could be made. An additional novel Two Dimensional (2D) optimisation technique based on thermal imaging data was created and used to calibrate the calculated heat transfer coefficients of the headslide of a small sized machine tool. In order to optimise the heat power of various heat sources, a 2D model of surface temperature of the headslide was created in Matlab software and compared against the experimental data both spatially across a plane and over time in order to take into account time varying heat loads. The effectiveness of the technique was proved using FEA models of the machine and comparison with test data from the machine tool. Significant improvement was achieved with correlation of 85 % between simulated thermal characteristics and the experimental data.

Manufacturing by mechanical machining has historically benefited from the use of cutting fluid. Cutting fluids help to reduce temperature, friction, flush away chips, and hence prolong tool life and improve machining performance. However, uncontrolled use of cutting fluid raises concern in respect of cost and environmental burden. For these reasons, dry machining is used in conjunction with high speed machining to reduce cycle times and simultaneously deliver a greener process. However, for some workpiece materials full implementation of dry machining is not economically viable due to the absence of the essential cooling and lubricating functions delivered by cutting fluids. The most feasible bridging technology is minimum quantity lubrication (MQL) where a very small flow rate of coolant/lubricant is delivered to the cutting zones. In terms of machinability, the application of MQL is promising. However, most studies conducted on MQL focused on the feasibility of MQL application and show-casing the technical benefits. No studies had been identified in literature systematically investigating the relationship between cutting conditions and MQL with the goal of optimising the process. Moreover, the presumed environmental benefits of MQL have not been systematically assessed because Life Cycle Analysis (LCA) derived evaluation models do not explicitly model the impact of machining conditions such as feedrates, cutting velocities and depth of cut.The motivation for this PhD work was to select the optimum machining process variables for maximising effectiveness of MQL, to explore process improvements and to assess the environmental credentials of the process in relation to other forms of cutting environments. In this work, high speed, end milling tests on tool steel were undertaken and 1) Taguchi methods were used to optimise the process, 2) the sensitivity of tool wear to nozzle position was evaluated and 3) the environmental burden of dry, MQL and flood coolants were evaluated based on direct energy needs and process outputs. A fluid soaking device was used to assess the amount of fluid collected or presumed to be delivered to the cutting zone for different nozzle orientations.The Taguchi process optimisation suggested that in HSM the size effect, brought about by a low chip thickness, should be considered in the search for an optimum process window for HSM. A significant and novel finding of this PhD was the dominance of MQL nozzle positioning. The study clearly showed that when machining hardened steel at a high cutting speed and RPM the tool life could be significantly increased by 50% by adjusting the position of the nozzle toward the rake face in relation to the end-milled face. The work opens up new science and provides recommendations as to where to align the nozzle when end milling tool steel at high cutting speeds. The fluid trapping and the blade-wiping angle are key parameters that influenced the effective delivery of MQL when high spindle revolutions per minute are used. These results from the fluid soaking device were found to correlate strongly with observed machining performance evaluations.In terms of modelling, the PhD developed an improved and more generic direct energy model that can be used to determine the environmental burden for direct electrical energy requirements and the energy embodied in other process material outputs. This model addresses the system boundary and activity that within the control of the manufacturing plant. The model was used to evaluate the environmental performance of dry, flood and MQL fluids. The impact of these results and models in optimising environmental performance was also illustrated.The work in this PhD is important to industry in that it contributes to the optimisation of MQL and gives an assessment of the environmental impact. The PhD developed new and significantly important machining science in the positioning of nozzles in MQL machining at higher speeds.