Gianni Campatelli

TL;DR: In this paper, the authors focus on the efficiency of machining centres and provide an experimental approach to evaluate and optimize the process parameters in order to minimize the power consumption in a milling process performed on a modern CNC machine.

TL;DR: In this article, a deep investigation of cutting force coefficient at different spindle speeds has been carried out, analyzing a wide range of spindles speeds: to overcome transducer dynamics issues, dynamometer signals have been compensated thanks to an improved technique based on Kalman filter estimator, two different coefficients identification methods have been implemented: the traditional average force method and a proposed instantaneous method based on genetic algorithm and capable of estimating cutting coefficients and tool runout at the same time.

TL;DR: In this article, the optimal selection of process parameters for wire arc additive manufacturing technology, an emerging solution for additive production of metal parts, is based on the evolution of the microstructure and on the mechanical properties of the final samples obtained through the successive deposition weld beads of a ER70S-6 steel.

TL;DR: In this paper, a novel heat source model is proposed based on the actual power distribution between filler and base materials, and an experimental validation is provided by comparing the measured distortions of a test case with the simulated ones, highlighting the accuracy of proposed model.

TL;DR: In this article, a finite element analysis of the thermal behavior of the workpiece is used to schedule the deposition of inter-layer idle times for wire-arc additive manufacturing process.