Titanium alloys are widely used in the manufacture of aircraft and aeroengine components. However, tool wear is a serious concern in milling titanium alloys, which are known as hard-to-cut materials. Trochoidal milling is a promising technology for the high-efficiency machining of hard-to-cut materials. Aiming to realize green machining titanium alloy, this paper investigates the effects of undeformed chip thickness on tool wear and chip morphology in the dry trochoidal milling of titanium alloy Ti–6Al–4V. A tool wear model related to the radial depth of cut based on the volume of material removed (VMR) is established for trochoidal milling, and optimized cutting parameters in terms of cutting speed and axial depth of cut are selected to improve machining efficiency through reduced tool wear. The investigation enables the environmentally clean rough machining of Ti–6Al–4V.

Accurate energy consumption modelling is critical for the improvement of energy efficiency in machining. Existing energy models of machining processes mainly focus on turning or milling, and there are few energy models for drilling. However, since drilling is often applied to roughing and semi-finishing, and the cutting parameters are large, the energy consumption is huge, and it is urgent to study the consumption of energy during the drilling process. In this paper, an energy consumption model for drilling processes was proposed. Idle power, cutting power, and auxiliary power were included in the proposed energy consumption model, using the cutting force to obtain the cutting power during drilling. Further, the relationship between cutting power and auxiliary power was analyzed. Cutting experiments were then carried out which confirmed the correctness of the proposed model. In addition, compared with several existing energy consumption models, the proposed model had better accuracy and applicability. It is expected that the proposed energy consumption model will have applications for the minimization of energy consumption and improvement of energy efficiency but not limited to only drilling energy consumption prediction.

A novel method for geometric model reconstruction of a damaged blade is presented to improve the precision machining of aero-engine blade repair. Based on the theoretical model of the blade, the iterative closest point (ICP) algorithm is used to determine the relationship between the measuring points and the theoretical model. Blade deformation mechanisms are analyzed to construct the fitting function of the blade deformation distribution and blade height. The spline interpolation method for local correction is then used to eliminate abrupt changes of the curvature, and it can guarantee the smoothness of the blending surface between the undamaged area and repaired area of the blade. The tool path is planned for the computerized numerical control (CNC) machining of the damaged area. A machining experiment of a repaired blade is carried out, and the machining results verify that the method presented in this paper is valid.