Energy consumption model for cutting operations in a stochastic environment

Nowadays, everyone agrees that it is urgent to reduce the consumption of energy and raw materials when manufacturing industries are concerned. Among all the transformation technologies, those related to chip removal are particularly interesting because of the high volume of processed material and because the final quality of the products largely depends on the fact that these processes correspond to the final stages of the production chain. Compromising the quality of the piece at this stage means not only discarding the piece but also losing the energy used to prepare the raw piece and to carry out the previous processes. Since unsuitable use of productive resources leads to a waste of time and money, in the past, many researchers have been developing models to optimize production processes by maximizing productivity and/or minimizing costs. Today, however, it is necessary to optimize the same processes from the total energy consumption point of view. Many authors already addressed this problem using a deterministic approach, when trying to identify the optimal cutting conditions. This means that tools are considered to be completely reliable elements in the production processes. The present work proposes an alternative methodology based on a stochastic approach to describe the tool resource; this approach is able to take into consideration the actual resources reliability and the consequent penalties deriving from their unpredicted failure, occurring before the expected replacement time.