The University of Manchester,Mohamad Farizal RAJEMI,Doctor of Philosophy,Energy analysis in turning and milling,2010.Energy generation as driven by consumption demand is a key contributor to carbon dioxide emissions and climate change. Hence reducing energy usage is an essential consideration in sustainable manufacturing. In addition, the world is experiencing a higher demand and cost of energy, hence reducing energy usage is an important factor for cost control and economic sustainability. Energy availability and security is now recognised as a key aspect to the socio-political sustainability of nations. Thus, reducing energy demand can be associated with the three; economic, environmental and social sustainability pillars. The manufacturing sector is a key industry that relies on the use of energy in driving value adding manufacturing processes. A widely used process is mechanical machining. This PhD was focussed on an investigation of energy consumption in machining processes and the energy footprints of machined products. A literature review had indicated that despite decades of optimising of machining operations based on cost and productivity, optimising energy use had not received significant attention. In the study a current monitoring device was used to evaluate current requirements and hence power and energy needs for machining processes. The study was done for (i) a range of workpiece materials and (ii) the turning and milling process. This enabled the definition of energy distribution for a machining process and identification of key areas of focus in order to reduce the energy used by a machine tool. The study was then focused on an energy intensive material in terms of machining requirements (titanium alloys) and an in-depth characterisation of the impacts of conventional compared to high speed machining was undertaken. From the study it was clear that a methodology was needed to ensure that energy use can be reduced or optimised. Thus an energy footprint model for a machined component was developed. This model was then used to derive an optimum tool life equation that satisfies the minimum energy criterion. A methodology for selection of optimum cutting conditions was then developed and tested on a component. Thus, the Thesis presents a new and novel model and methodology for selecting optimum cutting conditions for machining, based on minimum energy requirements. The energy savings associated with using such methodologies are quantified and found to be very significant. This work makes a distinct and important contribution to the machining science for reducing the energy and carbon footprints of machined products.