Optimizing cutting parameters for energy efficient CNC milling

Energy efficiency is a very important is- sue for a sustainable manufacturing. Machining of parts is a very time consuming process and it is di- rectly linked with the energy consumption and its ef- ficiency. The energy consumption depends on some process parameters such as spindle speed and feed rate. In cloud manufacturing environments, the de- ployed services can use cloud computing resources and parallelization power in order to optimize the cutting coefficients for the different machining operations in- side a machining task that better fit the user requests. First trials for the energy consumption reduction for part machining while saving Time and improving Ma- terial Removed Rate(MRR) is the aim of this work. For that, Spindle speed and Feed rate input param- eters have been analyzed from different simulations and multiobjective optimization approach has been considered. In the presented work, a simple use case has been performed and its results confirmed the cor- rectness of the approach taken into account