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.