Reducing energy consumption is a necessity towards achieving the goal of net-zero manufacturing. In this paper, the overall energy footprint of machining Ti-6Al-4V using various cooling/lubrication methods is investigated taking the embodied energy of cutting tools and cutting fluids into account. Previous studies concentrated on reducing the energy consumption associated with the machine tool and cutting fluids. However, the investigations in this study show the significance of the embodied energy of cutting tool. New cooling/lubrication methods such as WS2-oil suspension can reduce the energy footprint of machining through extending tool life. Cutting tools are commonly replaced early before reaching their end of useful life to prevent damage to the workpiece, effectively wasting a portion of the embodied energy in cutting tools. A deep learning method is trained and validated to identify when a tool change is required based on sensor signals from a wireless sensory toolholder. The results indicated that the network is capable of classifying over 90% of the tools correctly. This enables capitalising on the entirety of a tool’s useful life before replacing the tool and thus reducing the overall energy footprint of machining processes.
Recent global developments have heightened the need to choose the best sustainable manufacturing methods in order to mitigate the effects of industrial processes on the environment. Energy consumption is seen as one of the key performance indices for assessment of the environmental credentials of an enterprise. It is through energy consumption that the carbon emission penalty (amount of carbon emitted in generating the energy) can be estimated. Machining remains one of the key discrete-parts manufacturing processes and its mechanics has received considerable attention in research and development. However, energy analysis for machining processes is a relatively new area. In this paper the environmental impacts of machine utilisation are assessed through energy consumption. The paper considers the energy requirements in machining of a number of alloys according to recommended cutting conditions. The energy is accessed through electrical power requirements of the machining process. The results illustrate the impact that high speed machining could have on energy consumption and hence a more sustainable machining industry.
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