Explore the vast range of titles available.

This paper presented a new electrical discharge machining (EDM) method using powder mixed effects formed by the graphene–water dielectric to improve the machining performance in processing titanium alloy. Theoretical and simulation models were developed to analyze the effects of graphene bubbles on discharge breakdown characteristics and the plasma channel. To validate the theoretical model, single-pulse experiments were conducted by analyzing the shape and dimension of single-discharge craters. Comparative and exploratory experiments were carried out to investigate the erosion characteristics of the new machining approach. Experimental results show that graphene bubbles could affect the erosion characteristics and improve the machinability of titanium alloy. The material removal rate was increased by 28% and surface roughness was reduced by 55%, whereas relative electrode wear was reduced by 43% compared to traditional EDM processes.

Nickel-based alloys have great application value in aerospace, biomedical industry, chemical industry, and other fields. However, nickel-based alloys are known to be difficult to process, which will generate a lot of heat and friction during processing, which limits the application range of nickel-based alloys. Therefore, a large amount of cutting fluid needs to be used during processing, and the cutting fluid will cause harm to human health and the environment. In order to solve these problems, scholars proposed to use the minimum quantity lubrication (MQL) to replace the conventional flood cooling lubrication technique. Recently, many papers have proposed to use MQL for lubrication /cooling in the processing of nickel-based alloys. However, few studies have approached this topic comprehensively. To bridge this gap, this study conducts a comprehensive literature review of the progress made in the processing of nickel-based alloys using various MQL methods. It should be noted that these studies are divided into four categories: vegetable oil-based MQL, cryogenic cooling-based MQL, solid lubricant-based MQL, and electrostatic atomization-based MQL. It is crucial to compare the advantages of these cooling and lubricating technologies in machining nickel-based alloys, analyze their experimental results, and assess their impact on machining quality and tool wear. This review reveals that compared to traditional MQL, vegetable oil-based MQL is more energy-saving and environmentally friendly, resulting in approximately 30% improvement in surface quality and a 50% reduction in tool wear. The addition of solid lubricants to vegetable oil further enhances its lubrication performance. Cryogenic cooling-based MQL enables the attainment of finer grains and smaller sawtooth chips. Electrostatic atomization MQL, by altering the atomization process of traditional MQL, produces more uniform droplets, leading to a 42.4% reduction in tool wear and a 47% improvement in machined surface quality. The purpose of this paper is to help researchers identify existing gaps and to enable MQL to improve the processing quality and application range of nickel-based alloys. Finally, the present technical challenges and future research directions are put forward.

Wire electrical discharge machining (EDM) is the most important approach to cutting difficult-to-machine materials and components with complex shapes in the manufacturing industry. However, the multiple demands for high material removal rate, high surface quality, and low energy consumption require contradictory working conditions and restrict the further improvement of the performance of WEDM. This paper introduced a novel powder-mixed multi-channel WEDM method using the multi-channel discharge effect to meet the conflicting requirements. The multi-channel discharge effect utilizes the equipotential characteristics of the semiconductor powder mixed in the dielectric to disperse discharge energy and therefore provides a feasible solution to resolve the above contradictions. New working principles and machining mechanisms were discovered and verified by the simulation and experimental results. Comparative experiments show that the new powder-mixed multi-channel discharge WEDM method significantly reduced surface roughness and thermal defects while maintained a similar material removal rate as conventional WEDM.

There are a large number of holes to be machined on aeroengine components such as blisks, casings, etc. In order to ensure position accuracy, these holes usually need to be drilled continuously in one process. To ensure the machining quality of holes, either replacing the cutting tools in advance leads to an increase in manufacturing costs, or adjusting process parameters leads to a decrease in production efficiency, which is difficult to meet the requirements of efficient and low-cost manufacturing. In response to this issue, this paper proposes a multi-objective optimization strategy for the process parameters of porous continuous drilling of superalloys alloys. A unified mathematical model for multi-objective optimization of drilling parameters has been established, and a tool life prediction model based on machining parameters and a machining process energy consumption model have been established as objective functions. The proposed optimization strategy can select different optimization strategies for different optimization objectives, including: maximum tool life, minimum machining energy consumption, and multi-objective drilling parameter optimization. Finally, experimental verification was conducted on the proposed strategy, and the results showed that the proposed optimization strategy can significantly reduce drilling processing energy consumption and increase the service life of drilling tools.

The cutting characteristics observed in machining processes are significantly influenced by a combination of various dynamic parameters as well as the overall machine tool system in use. This paper introduces a cutting force coefficient mining method that considers the impact of tool vibration and machine tool system. Firstly, a basic cutting model was established based on orthogonal cutting. Obtained the cutting force coefficient for orthogonal cutting. Subsequently, the dynamic undeformed chip thickness data was integrated to reflect the influence of tool vibration during the machining process. Additionally, due to the replacement of the machine tool, correction factors have been introduced to consider the impact of the machine tool system. Finally, a comparative analysis was conducted with other methods for calibrating cutting force coefficients. The prediction accuracy of the proposed model has been validated, demonstrating its effectiveness in accurately predicting dynamic cutting forces.

In response to the difficulties in machining cemented carbide, this paper proposes a new approach to electrochemical milling of cemented carbide. A composite rotating tool cathode for electrochemical milling is designed, and the electric field simulation calculation is conducted for the electrochemical milling process. The electric field results show that as the tool cathode continues to penetrate, the machining area of electrochemical milling continues to increase, and the current density in the machining gap increases. After the tool cathode enters the semicircle, if the processing area of electrochemical milling remains unchanged, the amount of material removed per unit time remains unchanged, and the current density also remains stable. At the same time, orthogonal experiments and process parameter optimization were conducted on the electrochemical milling of cemented carbide side edges. The results showed that the maximum material removal was achieved under the process parameters of processing voltage 14 V, feed speed 10 mm/min, spindle speed 3000 r/min, and duty cycle of 70%. Based on the optimized process parameters of side-edge electrochemical milling, full edge electrochemical milling of experiment was carried out. When the feed rate is 0.3 mm/min, the surface of cemented carbide electrochemical milling is relatively flat and has a roughness of 0.389 μm.

Accurate power consumption models are the basis for improving energy efficiency of machine tools. The acquisition of energy consumption characteristics of different machine tools requires a large number of calibration experiments, which leads to low modelling efficiency. This paper proposes a rapid modelling method using transfer-learning to obtain the power consumption model of the target machine tool. After obtaining the power consumption model of the source machine tool through detailed experiments, this method only needs a few experiments to obtain the power consumption model of the target machine tool, which greatly improves the modelling efficiency, and the method is experimentally verified on different machine tools.

In the actual mechanical processing of difficult-to-process materials, normal or abnormal tool wear can lead to processing pauses or terminations, which seriously affects the processing accuracy and efficiency of workpieces, leading to workpiece scrapping. Therefore, predicting and monitoring tool wear during the actual machining process plays a crucial role in controlling tool costs and avoiding workpiece losses caused by tool wear. This paper proposed a tool wear prediction model based on power signals, which predicts tool wear by establishing a mapping between power signals and tool wear. Through drilling experiments for model calibration and validation, we verified that the proposed model can effectively predict tool wear under different parameters. In addition, based on the established prediction model, a real-time monitoring method for tool wear using power signals was proposed and implemented. Through experiments, it has been proven that the proposed method is suitable for monitoring normal and abnormal tool wear in actual machining.

Titanium alloy materials have been increasingly applied in the field of 3C products. Manufacturers in the production process of 3C products relentlessly pursue high production efficiency, resulting in extremely aggressive selection of process parameters. Extreme machining conditions such as high spindle speed and large feed speed inevitably lead to severe tool wear, making tool cost difficult to control. Therefore, this paper focuses on researching methods to improve the drilling performance and tool life of titanium alloy ultra-high-speed drilling bits, in order to achieve low-cost manufacturing of titanium alloy ultra-high-speed drilling. Firstly, the failure modes and wear mechanisms of drilling bits under ultra-high-speed drilling conditions for titanium alloy materials are analyzed. Secondly, a drilling bit simulation model is established and calibrated through drilling experiments. Then, using the response surface method, design simulation experiments to reveal the influence of geometric parameters on drilling performance and optimize the drilling bit. Finally, based on the optimization results, drilling bits are prepared and drilling performance and tool life experiments are conducted. A comparison with unoptimized bits shows that the optimized drilling bits have significant improvements in drilling performance and tool life.

The present volume comprises a collection of peer-reviewed papers covering manufacture and production, engineering materials, CAD/CAM/CAE, robotics, automation and control, environment-friendly design and manufacture, web/internet technologies, artificial intelligence and smart computing in design and manufacture, enterprise, management, and other related topics. This work will therefore be invaluable to production and research engineers, but also to research students and academics interested in the field.