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This work presents a method to optimize centerless grinding geometrical configuration. It is based on the regulation of the horizontal axes of operating and regulating wheels of the machine, coupled with an opportune blade profile, allowing a continuous selection of workrest angle and workpiece height, without requiring blade substitution and/or manual interventions. The regulation of workrest angle and height cannot be done independently: their relationship is defined during blade profile design. In machines with two independent axes for regulating wheel and blade horizontal displacement, this regulation can be performed in process or in the setup phase. This results in optimal processing parameter choice leading to improved quality and shorter processing time as well as reduced setup time.

This paper presents a novel approach for systematic energy efficiency evaluation and optimization in turning operations, combining spindle, chiller and material removal models. Framing a joint machine-process design approach, the proposed study aims at selecting optimal combinations of cutting parameters (feed rate, depth of cut and spindle speed) for a given spindle-chiller assembly, able to minimize the energy consumption. Contrary to most of the literature, where the efficiency analysis is fully empirical, relying on extended cutting test campaigns, here a model-based approach is adopted. The goal is to characterize a key subsystem of modern machine tools, often used in both turning and milling machines, composed by a permanent magnet brushless direct-drive spindle with a dedicated chiller unit. Analytical relationships are identified, producing efficiency maps as a function of various process parameters. Physic-based models are exploited, reproducing electrical and mechanical energy dissipation occurring in the spindle and chiller units and in the material removal process. The models parameters are identified by a reduced set of spindle ramp-up and cutting tests, executed in an industrial context. Then, an overall process efficiency optimization is performed and discussed.