Advances in Manufacturing最新文献

Wire electrochemical machining (WECM) is a potential method for manufacturing macrostructures from difficult-to-cut materials, such as turbine slots, with good surface integrity and low costs. In this study, a novel tube electrode with array holes in the front and insulation in the back was applied using WECM to improve the machining precision and efficiency. Additionally, assisted by an immersion electrolyte and axial flushing, the electrolyte-deficient gap was supplemented to achieve the cutting of a very thick workpiece. The simulation results indicated that this method could effectively reduce the machining gap and improve the uniformity of the electric- and flow-field distributions. Experiments verified that when the uninsulated range (machining angle) was reduced from 360° to 90°, the side machining gap was reduced from 462.5 µm to 175 µm. Finally, using optimized machining parameters, array slits with gaps as small as (175±10) μm were machined on a powder superalloy René 88DT sample with a thickness of 10 mm at a feed rate of 16 µm/s. The feasibility of fabricating complex profiles using this method was verified using a self-designed servo device.

Vertical centrifugal casting can significantly enhance the filling capability of molten metals, enabling the production of complex thin-walled castings at near-rapid cooling rates. In this study, the melt flow, solidification structures, and defects in 316 L steel cast strips with a geometry of 80 mm × 60 mm × 2.5 mm produced by vertical centrifugal casting were numerically and experimentally analyzed under different rotation speeds. With gradually increasing the rotation speed from 150 r/min to 900 r/min, the simulated results showed the shortest filling time and minimum porosity volume in the cast strip at a rotation speed of 600 r/min. Since a strong turbulent flow was generated by the rotation of the mold cavity during the filling process, experimental results showed that a “non-dendritic” structure was obtained in 316 L cast strip when centrifugal force was involved, whereas the typical dendritic structure was observed in the reference sample without rotation. Most areas of the cast strip exhibited one-dimensional cooling, but three-sided cooling appeared near the side of the cast strip. Moreover, the pores and cracks in the 316 L strips were detected by computed tomography scanning and analyzed with the corresponding numerical simulations. Results indicated the existence of an optimal rotational speed for producing cast strips with minimal casting defects. This study provides a better understanding of the filling and solidification processes of strips produced by vertical centrifugal casting.

Atomic and close-to-atomic scale manufacturing (ACSM) is the core competence of Manufacturing III. Unlike other conceptions or terminologies that only focus on the atomic level precision, ACSM defines a new realm of manufacturing where quantum mechanics plays the dominant role in the atom/molecule addition, migration and removal, considering the uncertainty principle and the discrete nature of particles. As ACSM is still in its infant stage, only little has been systematically elaborated at the core proposition of ACSM by now, hence there is a need to understand its concept and vision. This article elucidates the development of ACSM and clarifies its proposition, which aims to achieve a clearer understanding on ACSM and direct more effective efforts toward this promising area.

Keyhole tungsten inert gas (K-TIG) welding is capable of realizing single-sided welding and double-sided forming and has been widely used in medium and thick plate welding. In order to improve the accuracy of automatic weld identification and weld penetration prediction of robot in the process of large workpiece welding, a two-stage model is proposed in this paper, which can monitor the K-TIG welding penetration state in real time on the embedded system, called segmentation-LSTM model. The proposed system extracts 9 weld pool geometric features with segmentation network, and then extracts the weld gap using a traditional algorithm. Then these 10-dimensional features are input into the LSTM model to predict the penetration state, including under penetration, partial penetration, good penetration and over penetration. The recognition accuracy of the proposed system can reach 95.2%. In this system, to solve the difficulty of labeling data and lack of segmentation accuracy, an improved LabelMe capable of live-wire annotation tool and a novel loss function were proposed, respectively. The latter was also called focal dice loss, which enabled the network to achieve a performance of 0.933 mIoU on the testing set. Finally, an improved slimming strategy compresses the network, making the segmentation network achieve real-time on the embedded system (RK3399pro).

Ultrasonic rolling is an advanced non-cutting surface strengthening method that combines traditional rolling with ultrasonic vibration. In this research, the experiment of orthogonal end milling-ultrasonic rolling composite process has been carried out. The surface integrity refactoring changes and its mechanism of Ti-17 titanium alloy during the milling- ultrasonic rolling composite process has been studied and analyzed by the test and analysis of the surface geometric characteristics, residual stress, microhardness and microstructure before and after ultrasonic rolling. The residual stress and microhardness gradient distribution were characterized by cosine decay function and exponential decay function. All indicators of surface integrity were significantly improved after ultrasonic rolling. The study demonstrates that the reduction effect of the surface roughness by ultrasonic rolling process is inversely proportional to the initial surface roughness value. The ultrasonic rolling can only change the distribution form of the surface topography when the initial surface roughness is small. In addition, the improvement effect of ultrasonic rolling on surface compressive residual stress and microhardness decreased with the increase of initial milled surface roughness and surface compressive residual stress due to the factors such as energy absorption efficiency and mechanical properties changes of surface materials. A better ultrasonic rolled surface can be obtained by controlling the roughness and residual compressive stress of the initial milling surface to a small level.

In micro electrochemical machining (ECM) processes, stray corrosion causes undesired metal dissolution and the deterioration of shape accuracy. Adopting a sidewall-insulated electrode is an effective approach to suppressing stray corrosion. Most sidewall-insulated electrodes are made of metal substrate and non-metallic thin films. Nevertheless, the thin-film insulating materials attached to a metal substrate are susceptible to damage in an electrolytic environment. This study presents a novel concept of the conductive-material-filled electrode for better sidewall-insulation performance. The micro-scale quartz tube serves as the insulating substrate. Commercially available conductive fillers including metal wire, molten metals, and silver powder are filled inside the working cathode of the quartz tube. Consequently, the metal-wire-filled electrode, molten-metal-filled electrode, and nano-powder-filled electrode are designed and fabricated. From the verification results of electrode toughness, material removal rate, and surface topography, the metal-wire-filled electrode and molten-metal-filled electrode exhibit the same performance as a traditional metal-based electrode and much better durability. By contrast, the nano-powder-filled electrode is unable to withstand long-term ECM processes because of the loss of cured powder particles. In ECM experiments, microstructures with steep sidewalls (taper angle <9.7°) were machined using the metal-wire-filled electrode and molten-metal-filled electrode, which could replace the traditional electrode, achieving a longer service life and superior sidewall-insulation performance.

Micro-texturing has been widely proven to be an effective technology for achieving sustainable machining. However, the performance of micro-textured tools under different cooling conditions, especially their coupling effect on machined surface integrity, was scarcely reported. In this paper, the non-textured, linear micro-grooved, and curvilinear micro-grooved inserts were used to turn aluminum alloy 6061 under dry, emulsion, and liquid nitrogen cryogenic cooling conditions. The coupling effects of different micro-textures and cooling conditions on cutting force, cutting temperature, and machined surface integrity, including the surface roughness, work hardening, and residual stress, were revealed and discussed in detail. Results indicated that the micro-grooved tools, especially the curvilinear micro-grooved tools, not only reduced the cutting force and cutting temperature, but also improved the machined surface integrity. In addition, the micro-grooved tools can cooperate with the emulsion or liquid nitrogen to reduce the cutting force, cutting temperature, and improve the machined surface integrity generally, although the combination of emulsion cooling condition and micro-grooved tools generated negative coupling effects on cutting forces and surface work hardening. Especially, the combination of curvilinear micro-grooved cutting tools and cryogenic cooling condition resulted in the lowest cutting force and cutting temperature, which generated the surface with low roughness, weak work hardening, and compressive residual stress.

Possessing an efficient production line relies heavily on the availability of the production equipment. Thus, to ensure that the required function for critical equipment is in compliance, and unplanned downtime is minimized, succeeding with the field of maintenance is essential for industrialists. With the emergence of advanced manufacturing processes, incorporating predictive maintenance capabilities is seen as a necessity. Another field of interest is how modern value chains can support the maintenance function in a company. Accessibility to data from processes, equipment and products have increased significantly with the introduction of sensors and Industry 4.0 technologies. However, how to gather and utilize these data for enabling improved decision making within maintenance and value chain is still a challenge. Thus, the aim of this paper is to investigate on how maintenance and value chain data can collectively be used to improve value chain performance through prediction. The research approach includes both theoretical testing and industrial testing. The paper presents a novel concept for a predictive maintenance platform, and an artificial neural network (ANN) model with sensor data input. Further, a case of a company that has chosen to apply the platform, with the implications and determinants of this decision, is also provided. Results show that the platform can be used as an entry-level solution to enable Industry 4.0 and sensor data based predictive maintenance.

The dynamic force load in grinding process is considered as a crucial factor affecting the quality of parts, and a better understanding of the mechanism of force generation is conducive to revealing the evolution of material microstructure more precisely. In this study, an iterative blending integrating grinding force model that comprehensively considers the impact of grain size and dislocation density evolution of the material is proposed. According to the grinding kinematics, the interaction of grit-workpiece is divided into rubbing, plowing, and chip formation stages in each grinding zone. On this basis, the evolution of material microstructure in the current chip formation stage will affect the rubbing force in the next grinding arc through flow stresses, which in turn will influence the total grinding force. Therefore, the flow stress models in rubbing and chip formation stages are firstly established, and then the dislocation density prediction model is established experimentally based on the characteristics of grain size. The effects of the evolution of grain size and dislocation density on the grinding forces during the grinding process are studied by means of iterative cycles. The results indicate that the implementation of an iterative blending scheme is instrumental in obtaining a higher accurate prediction of the grinding force and a deeper insight of the influence mechanisms of materials microstructure on grinding process.

Fast drilling electrical discharge machining (EDM) is widely used in the manufacture of film cooling holes of turbine blades. However, due to the various hole orientations and severe electrode wear, it is relatively intricate to accurately and timely identify the critical moments such as breakout, hole completion in the drilling process, and adjust the machining strategy properly. Existing breakout detection and hole completion determination methods are not suitable for the high-efficiency and fully automatic production of film cooling holes, for they almost all depend on preset thresholds or training data and become less appropriate when machining condition changes. As the breakout and hole completion detection problems can be abstracted to an online stage identification problem, in this paper, a kurtosis-based stage identification (KBSI) method, which uses a novel normalized kurtosis to denote the recent changing trends of gap voltage signals, is developed for online stage identification. The identification accuracy and generalization ability of the KBSI method have been verified in various machining conditions. To improve the overall machining efficiency, the influence of servo control parameters on machining efficiency of each machining stage was analyzed experimentally, and a new stage-wise adaptive control strategy was then proposed to dynamically adjust the servo control parameters according to the online identification results. The performance of the new strategy is evaluated by drilling film cooling holes at different hole orientations. Experimental results show that with the new control strategy, machining efficiency and the machining quality can be significantly improved.