Energy efficient state control of machine tools: A time-based dynamic control policy

Machine state control is one of the most promising energy efficient measures for production processes. A proper control reduces the energy consumed during idle periods by switching off/on the machines, while a target productivity is assessed. However, a critical barrier for a practical implementation is related to the knowledge of part arrival process that is affected by uncertainty. Commonly, the stochastic processes involved in the system are assumed to be known. Instead, an effective policy should adapt itself to the environment conditions. This work provides an on-line time-based policy able to control the machine state while acquiring data. Through a method for the estimation of the stochastic parameters, the algorithm provides the optimal control parameters based on a certain set of observations. In order to prevent the implementation control parameters based on biased estimates, a new policy is formulated including the risk of incurring in high energy consumption. Potential benefits in terms of energy saving are significant and the effect on the production rate is discussed.