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The evolution of contact performance of electrical connectors, as an expression of service performance, played a significant role in various electronic equipment or system. However, very few methods had been used to detect the evolution of contact performance effectively and accurately. Hence, in this research, reliability accelerated testing was conducted to investigate the evolution of contact performance of electrical connectors. To detect the evolution of contact performance, contact resistance and friction and wear of the connector were measured using a DC resistance tester and an electron microscope respectively. Also, the effect of external conditions such as ambient temperature, mating speed, mating cycles was statistically investigated, and evolution curves were developed for contact resistance and abrasion loss. The obtained results revealed the temperature and mating speed affected the contact performance of electrical connectors. The increment of temperature reduced the shear strength of material and increased the thickness of oxide film. Increased mating speed greatly increased the probability of fracture of micro-protrusion due to collision, the wear form of connector had realized transition from low-speed adhesive wear to high-speed peeling wear. In addition, when the connector was mated about 3000 cycles, the contact performance of the connector would be greatly decreased.

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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.

Normal force is the dominant source of vibration in the linear permanent-magnet (LPM) machine. In order to investigate vibration of a new LPM vernier machine, normal pressure and their spatial harmonics are calculated by finite element method. Then, the natural vibration modes and transient displacement of the short mover is predicted. Finally, experimental result is given for verification. Results are instructive for design of a high precision and low vibration LPM machine.

Based on the finite element analysis software AdvantEdge, a simulation model for the milling process of aluminum alloy 7075-T7451was established to research the cutting temperature. This simulation model predicts the temperature distribution of work-piece and cutting tool, and the temperature variation trend along with the milling speed and rotational speed. The simulation results provide valuable references for researching on machining mechanism.

Based on a composited Newton–Cotes formula, this paper proposes a numerical method to predict milling stability considering regenerative chatter and focusing on rate and prediction accuracy. First, the dynamic model of milling motion is expressed as state-space equations considering regenerative chatter, with the tooth passing period divided into a set of time intervals. Second, a composited Newton–Cotes formula is introduced to calculate the transition function map for each time interval. Third, the state transition matrix is constructed based on the above-mentioned transition function, and the prediction stability boundary is determined by the Floquet theory. Finally, simulation analysis and experimental verification are conducted to verify the effectiveness of the proposed method. The simulation results demonstrate that, for the milling model with a single degree of freedom (DOF), the convergence rate and prediction accuracy of the proposed method are higher than those of the comparison method. The experimental results demonstrate that, for the milling model with two DOFs, the machining parameters below the prediction stability boundary can avoid the chatter as much as possible, ensuring the machined surface quality.