In order to improve the cutting performance in broaching, the lubrication and cleaning effects offered by water-based cutting fluids with green additives need to be studied from the viewpoint of green manufacturing. Therefore, water-based solutions with castor oil, surfactant (linear alkylbenzene sulfonate, LAS), and nanographite were prepared by ultrasonic agitation and sprayed into the zone of broaching via atomization. The performances of the cutting fluids, in terms of the viscosity, specific heat, wetting angle, and droplet size, were evaluated to discuss their effects on the broaching load. Among the fluids, the addition of LAS into oil-in-water (WO-S), where its cutting fluid with 10 wt.% castor oil and 1.5 wt.% surfactant, exhibited the lowest broaching force. With regard to the lubricating and cleaning mechanisms, WO-S has good wettability and permeability, and hence, can lubricate the cutting edge of the tool to decrease the cutting load, cool the cutting edge to keep it sturdy, and clean the surface of the cutting edge to keep it sharp. The results reveal that the simultaneous addition of castor oil and LAS had remarkable effects on the lubrication and cleaning, and resulted in a broaching load reduction of more than 10% compared to commercial cutting fluids. However, the addition of nanographite could not improve the lubrication owing to its agglomeration.

Robotic milling has broad application prospects in many processing fields. However, the milling performance of a robot in a certain posture, such as in face milling or grooving tasks, is extremely sensitive to process parameters due to the influence of the serial structure of the robot system. Improper process parameters are prone to produce machining defects such as low surface quality. These deficiencies substantially decrease the further application development of robotic milling. Therefore, this paper selected a certain posture and carried out the robotic flat-end milling experiments on a 7075-T651 high-strength aeronautical aluminum alloy under dry conditions. Milling load, surface quality and vibration were selected to assess the influence of process parameters like milling depth, spindle speed and feed rate on the milling performance. Most notably, the contribution ratio based on the analysis of variance (ANOVA) was introduced to statistically investigate the relation between parameters and milling performance. The obtained results show that milling depth is highly significant in milling load, which had a contribution ratio of 69.25%. Milling depth is also highly significant in vibration, which had a contribution ratio of 51.41% in the X direction, 41.42% in the Y direction and 75.97% in the Z direction. Moreover, the spindle speed is highly significant in surface roughness, which had a contribution ratio of 48.02%. This present study aims to quantitatively evaluate the influence of key process parameters on robotic milling performance, which helps to select reasonable milling parameters and improve the milling performance of the robot system. It is beneficial to give full play to the advantages of robots and present more possibilities of robot applications in machining and manufacturing.

In this paper, a new model of cutting grinding force for disc wheels is presented. Initially, it was proposed that the grinding cutting force was formed by the grinding force and cutting force in combination. Considering the single-grit morphology, the single-grit average grinding depth, the effective number of grits, and the contact arc length between the grit and the workpiece comprehensively, the grinding force model and the cutting force model were established, respectively. Then, a universal grinding cutting force model was optimized by introducing the effective grit coefficient model, dependent on the probability statistical method and the grit height coefficient model with Rayleigh’s distribution theory. Finally, according to the different proportions of the grinding force and cutting force, the grinding cutting force model, with multi-particles, was established. Simulation and experimental results based on piezoelectric sensors showed that the proposed model could predict the intermittent grinding cutting force well. Moreover, the inclusion of the grit height coefficient and the effective grits number coefficient improved the modeling accuracy. The error between the simulation and experimental findings in grinding cutting force was reduced to 7.8% in comparison with the traditional model. In addition, the grinding cutting force can be divided into three segments; increasing, steadiness, and decreasing, respectively found through modeling.

Milling plays a significant role in the machining of aluminum alloy parts. However, in the milling process, the material easily adheres to the tip of the milling tool due to the high ductility and thermal deformation of the aluminum alloy; the machining efficiency and quality are hard to further improve. Hence, in order to promote the machining performances, three textures (linear, wavy, and micropitted) are prepared, respectively, on rake face of milling tools using the laser processing system. Then, milling load, top‐burrs, and surface quality are chosen to discuss the machining performance of textured milling tools. In particular, the top‐burrs are investigated by relative area ratio of top‐burrs (RARB) which is calculated from the micrograph after binarization. The obtained results evidently show that the wavy textured milling tool reduces the milling load by an amount of 10.7% compared to the nontextured milling tool. This is due to the smaller contact area that reduces the internal friction of the tool‐chip contact area and thus reduces the load. And surface roughness improves by an amount of 23.8% because the wavy texture has the largest proportion of the unit area, and it can effectively improve the storage capacity of debris. Therefore, the wavy texture proposed in this research is of great reference value for the optimization of the machining performance of the milling tool.

The optimization of a broach surface is of great significance to improve the cutting performance of the tool. However, the traditional optimization method (surface texture, coating, etc.) destroys the stress distribution of the tool and reduces the service life of the tool. To avoid these problems, four kinds of flocking surfaces (FB1, FB2, FB3, and FB4), imitating the biological structure of Daphniphyllum calycinum Benth (DCB), were fabricated on the rake face of the broach by electrostatic flocking. The broaching experiment, wettability, and spreading experiment were then conducted. Moreover, the mathematical model of the friction coefficient of the bionic broach was built. The effect of broaches with different flocking surfaces on the broaching force, chip morphology, and surface quality of workpieces was studied. The results indicate that the flocked broaches (FB) with good lubricity and capacity of microchips removal (CMR) present a smaller cutting force (F_c) and positive pressure (F_t) compared to the unflocked broach (NB), and reduce the friction coefficient (COF). The chip curl was decreased, and the shear angle was increased by FB, which were attributed to the function of absorbing lubricant, storing, and sweeping microchips. Its vibration suppression effect enhanced the stability in the broaching process and improved the surface quality of the workpiece. More importantly, the FB2 with the most reasonable fluff area and spacing exhibited the best cutting performance. The experimental conclusions and methods of this paper can provide a new research idea for functional structure tools.