Advances in Manufacturing最新文献

Ti₂AlNb intermetallic alloys, which belong to the titanium aluminum (TiAl) family, are currently being extensively researched and promoted in the aerospace industry because of their exceptional properties, including low density, high-temperature strength, and excellent oxidation resistance. However, the excellent fracture toughness of the material leads to the formation of surface defects during machining, thereby affecting the quality of the machined surface. In this study, Ti₂AlNb intermetallic alloys were subjected to side-milling trials to investigate the influence of tool coating and tool wear on both the machined surface quality and chip morphology. Specifically, the tool life, machined surface roughness, surface morphology, surface defects, and chip morphology were investigated in detail. The results indicated that the tool coating provided a protective effect, resulting in a threefold increase in the service life of the coated end mill compared to that of the uncoated one. A coated end mill yields a superior machined surface topography, as evidenced by reduced roughness and a more consistent morphology. Tool wear has a significant effect on the morphology of machined surfaces. The occurrence of material debris and feed marks became increasingly severe as the tool wore off. The chip morphology was not significantly affected by the tool coating. However, tool wear results in severe tearing along the chip edge, obvious plastic flow on the non-free surface, and a distinct lamellar structure on the free surface.

In the era of Industry 4.0, robot motion planning faces unprecedented challenges in adapting those high-dimension dynamic working environments with rigorous real-time planning requirements. Traditional sampling-based planning algorithms can find solutions in high-dimensional spaces but often struggle with achieving the balance among computational efficiency, real-time adaptability, and solution optimality. To overcome these challenges and unlock the full potential of robotic automation in smart manufacturing, we propose bidirectional recurrent motion planning network (BRMPNet). As an imitation learning-based approach for robot motion planning, it leverages deep neural networks to learn the heuristics for approximate-optimal path planning. BRMPNet employs the refined PointNet++ network to incorporate raw point-cloud information from depth sensors and generates paths with a bidirectional strategy using long short-term memory (LSTM) network. It can also be integrated with traditional sampling-based planning algorithms, offering theoretical assurance of the probabilistic completeness for solutions. To validate the effectiveness of BRMPNet, we conduct a series of experiments, benchmarking its performance against the state-of-the-art motion planning algorithms. These experiments are specifically designed to simulate common operations encountered within generic robotic platforms in smart manufacturing such as mobile robots and multi-joint robotic arms. The results demonstrate BRMPNet’s superior performance on key metrics including solution quality and computational efficiency, suggesting the promising potential of learning-based planning in addressing complex motion planning challenges.

Currently quality information management of the ready-mixed concrete (RMC) is manually operated, facing risks like poor traceability, information tampering, and fragmentation in the RMC supply chain. To this end, this study proposes a Blockchain-IPFS (interplanetary file system)-enabled information management platform for improving transparency, traceability, and effectiveness of RMC quality management. Specifically, through a semi-structured interview investigating the potential benefits and applications of Blockchain, a transformative Blockchain-based management mode for RMC quality management is constructed. Based on that, a novel Blockchain-based architecture is further proposed by integrating with IPFS and cloud service for addressing its data storage limitation. Furthermore, the information flows and smart contracts representing physical and cyber interactions among multiple supply chain stakeholders are illustrated in detail. Finally, a real-world case study is presented to verify the feasibility of the proposed model. A prototype system is established with solutions for client-cloud collaboration, multi-source data fusion, and enterprise privacy protection, detailing the practical application of proposed model in actual projects. The evaluation results indicate that the proposed model can improve the quality management of RMC supply chain from three aspects: transparency, traceability, and information sharing. This paper contributes to the body of knowledge by offering a novel architecture leveraging both Blockchain and IPFS in storing small-sized and large-sized information. Meanwhile, this research moves beyond conceptual framework and implements the theoretical benefits of Blockchain into engineering practice. Technical components in this paper can be adapted for multiple applications in the construction industry, providing valuable references for future search efforts.

Ultrasonic impact significantly influences the mechanical properties and flow stress of Ti-17 titanium alloy. In this study, compression tests on Ti-17 titanium alloy were conducted under ultrasonic impact conditions, varying ultrasonic amplitudes and compression rates. The flow stress, surface elemental content, microhardness, and microstructure of Ti-17 titanium alloy were tested, and the softening mechanism of Ti-17 titanium alloy under ultrasonic impact conditions was investigated. The results indicate that the softening mechanism of Ti-17 titanium alloy involved ultrasonic softening combined with stress superposition. Ultrasonic impact leads to a higher distribution of grain orientation differences, alters the distribution of small-angle grain boundaries, and changes the distribution of surface phases, resulting in a reduced density of α phases. The geometrically necessary dislocation density at the surface increases, and the average grain size decreases from 2.91 μm to 2.73 μm. The Brass-type texture essentially disappears, transforming mainly into a Copper-type texture {112}<11-1>, with the maximum pole density decreasing from 73.98 to 39.88.

There are a large number of low rigidity parts in the aerospace field, and how to achieve high-performance manufacturing in their multistage machining processes has received increasing attention. Optimizing the distribution of machining allowance and machining parameters is one of the most convenient ways to improve the machining performance of these parts. In this paper, firstly, considering the machining accuracy and machining efficiency comprehensively, the error efficiency cooperation coefficient of low rigidity parts during machining is established. Based on the semi-parametric regression theory and measured data, the machining error transfer factor within the cooperation coefficient is calibrated. Secondly, the machining optimization strategy based on the Bayesian framework is proposed, and the optimization of multiple machining parameters is realized with the goal of minimizing the error efficiency cooperation coefficient. Finally, the optimization software of machining processes of low rigidity parts for engineering application is developed. In the verification experiments of blade parts, the error efficiency cooperation coefficient is reduced to 0.032 1 after optimization, and the average improvement of machining errors of all measured points is (14.31,{upmu {text{m}}}). Besides, the above method is applied to low rigidity shaft parts, and the effectiveness of the proposed method is further verified.

High-speed grinding (HSG) is an advanced technology for precision machining of difficult-to-cut materials in aerospace and other fields, which could solve surface burns, defects and improve surface integrity by increasing the linear speed of the grinding wheel. The advantages of HSG have been preliminarily confirmed and the equipment has been built for experimental research, which can achieve a high grinding speed of more than 300 m/s. However, it is not yet widely used in manufacturing due to the insufficient understanding on material removal mechanism and characteristics of HSG machine tool. To fill this gap, this paper provides a comprehensive overview of HSG technologies. A new direction for adding auxiliary process in HSG is proposed. Firstly, the combined influence law of strain hardening, strain rate intensification, and thermal softening effects on material removal mechanism was revealed, and models of material removal strain rate, grinding force and grinding temperature were summarized. Secondly, the constitutive models under high strain rate boundaries were summarized by considering various properties of material and grinding parameters. Thirdly, the change law of material removal mechanism of HSG was revealed when the thermodynamic boundary conditions changed, by introducing lubrication conditions such as minimum quantity lubrication (MQL), nano-lubricant minimum quantity lubrication (NMQL) and cryogenic air (CA). Finally, the mechanical and dynamic characteristics of the key components of HSG machine tool were summarized, including main body, grinding wheel, spindle and dynamic balance system. Based on the content summarized in this paper, the prospect of HSG is put forward. This study establishes a solid foundation for future developments in the field and points to promising directions for further exploration.

Owing to their brittleness and heterogeneity, achieving carbon fiber-reinforced silicon carbide ceramic (C_f/SiC) composites with ideal dimensional and shape accuracy is difficult. In this study, unidirectional C_f materials were subjected to orthogonal grinding experiments using different fiber orientations. Through a combined analysis of the surface morphology and grinding force after processing, the mechanism underlying the effect of the fiber orientation on the surface morphology of the material was explained. The surface roughness of the material was less affected by the process parameters and fluctuated around the fiber radius scale; the average surface roughness (R_a) in the direction of scratching parallel (SA) and perpendicular (SB) to the fiber direction was 4.21‒5.00 μm and 4.42‒5.26 μm, respectively; the material was mainly removed via the brittle removal mechanism; and the main defects of the fiber in the SA direction were tensile fracture and extrusion fracture; the main defects of the fiber in the SB direction were bending fracture, shear fracture, and fiber debonding. The grinding parameters influenced the grinding force in the order: depth of cut > feed rate > wheel speed. The grinding force increased with an increase in the feed rate or depth of cut and decreased with an increase in the wheel speed. Moreover, increasing the depth of cut was more effective in decreasing the grinding force and improving the material removal efficiency than adjusting the rotational speed of the workpiece and the rotational speed of the grinding wheel. The specific grinding energy decreased with an increase in the feed rate or depth of cut, and increased with an increase in the grinding wheel speed.

Electrical arc machining (EAM) is an efficient process for machining difficult-to-cut materials. However, limited research has been conducted on sloped surface machining within this context, constraining the further application for complex components. This study conducts bevel machining experiments, pointing out that the surface quality becomes unsatisfactory with the increasing bevel angle. The discharge condition is counted and analyzed, while the flow field and the removed particle movement of the discharge gap are simulated, demonstrating the primary factor contributing to the degradation of surface quality, namely the loss of flushing. This weakens both the plasma control effect and debris evacuation, leading to the poor discharge condition. To address this issue, the magnetic field is implemented in blasting erosion arc machining (BEAM). The application of a magnetic field effectively regulates the arc plasma, enhances debris expulsion, and significantly improves the discharge conditions, resulting in a smoother and more uniform sloped surface with a reduced recast layer thickness. This approach provides the possibility of applying BEAM to complex parts made of difficult-to-cut materials in aerospace and military industries.

The precision, lifespan, and stability of the electro-hydraulic servo valve sleeve are significantly impacted by the edge burrs that are easily created when honing the valve sleeve. The existing deburring process mainly rely on manual operation with high cost and low efficiency. This paper focuses on reducing the burr size during the machining process. In this paper, a single-scratch test with a finite element simulation model is conducted to study the mechanism of burr generation. The tests were carried out under ultrasonic vibration and non-ultrasonic vibration conditions to explore the effect of ultrasonic vibration on burrs. Besides, a honing experiment is conducted to verify the conclusions. The results at various cutting parameters are analyzed, and the mechanism of burr generation is revealed. The stiffness lacking of the workpiece edge material is the main reason for the burr generation. The cutting depth shows a significant effect on burr size while the cutting speed does not. The inhibition mechanism of ultrasonic vibration on burrs is also revealed. The separation of the burr stress field under ultrasonic vibration and the higher bending hinge point is the reason for burr fracturing. The re-cutting effect of ultrasonic vibration reduces the burr growth rate. The results of the honing experiment verified these conclusions and obtained a combination of honing parameters to minimize the burr growth rate.

High precision and minimal noise are considered critical performance measures for top-tier gear transmission systems. To ensure optimum gear trans mission performance, the tooth surface texture should be enhanced without comparing the gear precision. By integrating the principle of internal gearing power honing with tooth surface topology modifications, the adjusted honing texture can be forecasted, and proactive control can be achieved, both of which are considered as crucial for the reduction of gear vibration and noise. In this study, a manufacturing technique for high-order modified helical gears is introduced. The formation rules and modeling of the honing texture are explored, leading to a novel method for three-dimensional modeling and control of the altered honing texture. The direction of the cutting speed of abrasive grains at the contact point between the honing wheel and working gear tooth surface was examined. Using the discrete abrasive grain motion trajectory method, the honing texture was produced, through which the formation mechanisms and control strategies of the curved honing texture were illuminated. Based on these findings, a method for flexible topology modifications of the tooth surface is suggested. This is achieved by adjusting the motion coefficients of each axis of the honing machine and adding additional motion in the form of higher-order polynomials to three motion axes, including the radial feed and oscillation axes of the honing wheel and the interleaved axes of the work gear and honing wheel. A least-squares estimation method, based on a sensitivity matrix, was employed to determine the additional motion coefficients. By this method, the texture of the modified tooth surface can also be predicted and controlled. In a numerical example, the efficacy of the flexible topology modification method was confirmed. In this case, the altered honing texture was managed by modifying the axis intersection angle, while the accuracy of tooth surface modifications was maintained. This study has theoretical and application value in the field of gear manufacturing, oriented to the demand for gear vibration and noise reduction functions.