Ti-6Al-4V is widely used in the aerospace, automobile, and biomedical fields, but is a difficult-to-machine material. Electrical discharge machining (EDM) is regarded as one of the most effective approaches to machining Ti-6Al-4V alloy, since it is a non-contact electro-thermal machining method, and it is independent from the mechanical properties of the processed material. This paper aims to combine grey relational analysis and Taguchi methods to solve the problem of EDM parameters optimization. From the viewpoint of health and environment, tap water as working fluid has good working environment, since it does not release harmful gas. The process parameters include discharge current, gap voltage, lifting height, negative polarity and pulse duty factor. The electrode wear ratio (EWR), material removal rate (MRR) and surface roughness (SR) as objective parameters are chosen to evaluate the whole machining effects. Experiments were carried out based on Taguchi L 9 orthogonal array and grey relational analysis, and then verified the results through a confirmation experiment. Compared the machining parameters A 1 B 1 C 3 D 2 with A 1 B 2 C 2 D 2 , MRR increased from 1.28 mm 3 /min to 2.38 mm 3 /min, EWR decreased from 0.14 to 0.10 mm 3 /min and SR decreased from Ra 2.37 μm to Ra 1.93 μm. The process parameters sequenced in order of relative importance are: the ratio of pulse width to pulse interval, discharge current, lifting height and gap voltage. The results showed that using tap water machining Ti-6Al-4V material can obtain high MRR, decrease the machining cost and have no harmful to the operators and the environment.

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Ceramic particle-reinforced metal matrix composites (PRMMCs) have been widely applied in modern industry with excellent mechanical characteristics. Meanwhile, the addition of high hardness reinforcements also produces a significant challenge for precision machining of PRMMCs and leads to poor machinability and higher time consumed in the subsequent surface treatment process. To investigate the machining mechanism of PRMMCs, a 2D mesoscopic-based finite element (FE) model reinforced with randomly distributed polygon particles was developed. Elastoplastic and failure behavior of aluminum alloy, high hard-brittle and fracture characteristics of reinforcements and particle-matrix-tool interactions were considered comprehensively. Systematic cutting experiments show that the proposed FE model accurately predicts deformation mechanism and surface quality of PRMMCs. Particle fracture and debonding are mainly determined by the stress distribution and strain value. Serrated chips primarily are formed along shear plane and accompanied with the generation and propagation of microcracks. In addition, cracks around particles are easier to propagate to chip root and promote the formation of segmented chips. Cutting depth significantly affects the surface quality, subsurface damage, and cutting force. Moreover, a proper cutting speed is beneficial to improve efficiency and machinability of PRMMCs. Keywords Ceramic particle • Metal matrix composites • Precision machining • Deformation mechanism • Finite element analysis AbbreviationsYield stress (MPa) t Tensile stress (MPa) cCompressive stress (MPa) 0

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Abstract. Elliptical vibration cutting (EVC), as a precision machining technology, is used in many applications. In precision machining, control accuracy plays an essential role in improving the machinability of difficult-to-machine materials. To improve the control accuracy, dynamic and static characteristics of the system need to be tuned to obtain the optimal parameters. In this paper, we use a glowworm algorithm with an improved adaptive step size to tune the parameters of a robust adaptive fuzzy controller. We then obtain the optimal controller parameters through simulation. The optimal solution of the controller parameters is then applied to a 3D EVC system model for simulation and closed-loop testing experiments. The results indicate that a good agreement between the ideal curve and the tracking signal curve verifies the optimality of the controller parameters. Finally, under certain cutting conditions, the workpieces of three different materials are cut with two different cutting methods. The study revealed that the surface roughness value is reduced by 20 %–32 %, which further verifies the effectiveness of the optimal controller's parameters.

Three-dimensional elliptical vibration assisted cutting technology has been widely used in the past few years. The piezoelectric stack drive structure is an important part of the three-dimensional elliptical vibration aided cutting system. Its piezoelectric hysteresis characteristics affects the final output of the elliptical trajectory. Aiming at this problem, a piezoelectric hysteresis modeling method based on a generalized Bouc–Wen model is presented in this paper. An improved flower pollination algorithm (IFPASO) was used to identify Bouc–Wen model parameters. Standard test result shows that IFPASO has better algorithm performance. The model identification effect experiment proved that the Bouc–Wen model obtained by IFPASO identification, the highest modeling accuracy of the three axial subsystems, can reach 98.86%. Therefore, the model can describe the piezoelectric hysteresis characteristics of the three axial subsystems of the 3D-EVC system effectively and has higher modeling accuracy and fitting accuracy.