CIRP Journal of Manufacturing Science and Technology最新文献

Lattice metamaterials, a class of structures utilized for geometric lightweighting and enhancing structural integrity, feature interconnected elements arranged in specific patterns. These patterns confer unique properties beneficial for improving stiffness, damping, energy absorption, and strength across various applications. However, computational simulation of lattice structures for design and optimization presents significant challenges due to nonlinear and elastic/inelastic effects like instabilities, contacts, rate-dependence, and plasticity. Current methods heavily rely on finite element analysis (FEA), yet they entail high computational complexity and do not fully align with experimental observations. Moreover, additive manufacturing (AM) technologies introduce additional computational complexity due to process-induced anisotropic behaviors. This paper proposes a computational model to construct an effective descriptor by integrating metamaterial topological information with AM conditions. This descriptor serves as a surrogate for FEA models. Additionally, a database is established to correlate the descriptor with experimentally acquired mechanical responses of additively manufactured metamaterials. The bidirectional operation of the envisaged descriptor fulfills two objectives: informing the mechanical response of novel metamaterial models and guiding design and AM processes based on desired outcomes. Model validation demonstrates significant concurrence between predicted and experimental results, evidencing the model's capability to capture inherent nonlinearity in both design and process.

In the realm of five-axis Computer Numerical Control (CNC) machining, the challenge of minimizing velocity, acceleration, and jerk fluctuations has prompted the development of various local corner smoothing methods. However, existing techniques often rely on symmetrical spline curves or impose pre-set transition length constraints, limiting their effectiveness in reducing curvature and maintaining velocity at critical corners. To comprehensively address these limitations comprehensively, a novel approach for local smoothing of five-axis linear toolpaths is presented in this paper. The proposed method introduces two asymmetrical B-splines at corners, effectively smoothing both the tool-tip position in the workpiece coordinate system and the tool orientation in the machine coordinate system. To fine-tune transition curve scales and minimize velocity disparities between adjacent corners, an overlap elimination scheme is employed. Furthermore, the two-step strategy emphasizes the synchronization of tool-tip position and tool orientation while considering maximal approximation error. The outcome is a blended five-axis toolpath that significantly reduces curvature extremes in the smoothed path, achieving reductions ranging from 36.28 % to 45.51 %. Additionally, the proposed method streamlines the interpolation process, resulting in time savings ranging from 5.68 % to 8.78 %, all the while adhering to the same geometric and kinematic constraints.

Irregular (i.e. non-spherical) morphology powder is more cost-efficient to produce than spherical shaped powder. However, its reduced levels of flowability limit the wide application ranges of laser beam powder bed fusion (LPBF). To address this issue, a novel powder sheet additive manufacturing concept (MAPS) is proposed. Herein, a pre-manufactured metal particle-polymer binder composite (i.e. powder sheet) feedstock is employed as a raw material. The printability of irregularly shaped powder particles in sheet (MAPS) format was physically investigated using a range of different process parameters. The manufacturing process was observed by high-speed imaging. Microstructural and chemical element characterisations of the irregularly shaped powder particle print were then compared against those prints which were conducted using sheet-based (MAPS) spherical powder morphologies. The results indicated that the geometric accuracy and density of irregular powder morphology sheet printing improved when using a negative defocus strategy of the laser beam. A negative defocusing strategy allowed for the melting mode of the material to be transformed from keyhole to a more favourable conduction state. High speed imaging revealed that more spatter and vapour plume were observed with the increase in the magnitude of the negative defocus. The multi-morphology 304 L stainless steel (SS304) samples were printed in a single printer using an efficient method for the first time, i.e. printing spherical SS304 material on top of irregular SS304. EDX results indicated an insignificant change of chemical elements between the spherical and irregular prints. EBSD results revealed that columnar grains could grow through the irregular-spherical transition zone and similar grain size can form between spherical and irregular prints. The results of this study provide insights into the optimum printing configurations for powder sheet additive manufacturing using a cost-effective solution of irregular morphology material.

Arc weaving is a feasible technique for making thick-walled components in the arc-based directed energy deposition process (DED-Arc). In the current study, four different arc weaving strategies, namely, triangle, square, semi-circle, and helix, are used to fabricate the walls. For this, gas tungsten arc welding (GTAW) based DED-Arc set-up using aluminium alloy wire (ER4043) as a filler material is used for different printing strategies. The fabricated walls were investigated for their surface characteristics, microstructure, mechanical properties and residual stress. The weld-bead and wall geometry study revealed that for the same number of layers, the semi-circular arc-weaving strategy had the maximum height among all, with an effective area of 65.77 %. The waviness of the side surface of the walls was maximum for the semi-circle (714 ± 35 µm), indicating the semi-circle will require almost twice the amount of machining than the helix, square, and triangle in postprocessing operation. The optical micrographs showed that the semi-circular weaving pattern exhibited a coarser gain with thicker grain boundaries with an average grain size of 46.4 ± 23.7 µm as compared to other weaving patterns. The triangle weaving pattern demonstrated the smallest grain size among all, resulting in high hardness and superior wear resistance. The residual stress (RS) results revealed that the RS is in tension (22–24 MPa) in the bottom layers for all the walls and becomes almost zero (−1.5 to −2.5 MPa) in the top layers except for the walls formed by helix strategy. The square weaving strategy strikes a balance between surface characteristics, microstructure, and mechanical properties, making it a highly viable option for thick wall fabrication.

Despite the many advantages that additive technologies have over subtractive ones, low porosity levels, good mechanical properties, and low residual stresses remain the most pressing issues that need further research. In particular, the latter can cause a mismatch between the desired geometry and the geometry that can be achieved. In this work, a process window for the Laser Powder Bed Fusion (LPBF) process of Ti-6Al-4V alloys, has been identified. The micro-warping phenomenon, which causes the deformation of the printed part during the printing job and the failure of the process, was taken into account together with the parts' strength, ductility, and porosity. The occurrence of micro-warping phenomena was assessed by the new Warping Alert (WA) parameter, which depends on the parameters P and v. It was found that, before balling, micro-warping limits the process window in the laser power (P) – laser velocity (v) plane. However, optimal mechanical performances can be found in the proximity of the micro-warping zone, thus making it extremely important to determine the WA threshold value to the process design.

For the problems of instability and low forming quality in the profiled ring rolling process of large aluminum alloy ring, a method for profiled ring rolling based on position/force feedback was proposed. Based on the data of position and pressure sensor, the control strategy of guide roll and axial roll was developed. On the other hand, a mixed feeding strategy about "constant feed speed of mandrel"(CFSM) to "constant growth of ring radius"(CGRR) is provided. By using ABAQUS/CAE analysis software and Fortran language, a finite element model (FEM) for simulation profiled ring rolling process of large aluminum alloy considering position/force feedback control was established, and the rolling stability and forming quality in profiled rolling process were analyzed. The results of simulation and experiment show that under the condition of rolling stability, the cross section and outer radius of ring meet the design requirements, and the center displacement and roundness errors of ring are reduced by 75%.

X-ray computed tomography (XCT) has been shown to be a reliable tool for quality inspection, material evaluation, and dimensional measurement tasks across diverse academic and industrial applications. In recent years, the integration of machine learning and deep learning techniques have ushered new advances in the industrial computed tomography domain spanning multiple facets, including image reconstruction, segmentation, and feature characterization. This review paper comprehensively surveys the current state-of-the-art machine learning and deep learning applications throughout the entire XCT workflow. Additionally, we explore relevant developments in the medical imaging domain, evaluating their implications for industrial computed tomography. In conclusion, we identify potential future research, drawing insights from existing research gaps in the domain and recent advancements in artificial intelligence. Notably, we underscore the importance of uncertainty quantification and model explainability for further acceptance of artificial intelligence techniques in the domain.

A novel multi wire feed mechanism has been introduced and investigated for tungsten-inert-gas-based wire arc additive manufacturing (WAAM-TIG) method to minimise the dependency of wire feed direction. The concurrent three wire feed mechanism mounted 120° apart around the TIG torch was developed by employing three independent wire feeders, and an integrated effect of front-back-side feeding minimised the dependency of the wire feeding direction on the deposited bead. The mechanism was compared with the single wire feed, and geometrical uniformity, material deposition rate and overall specific energy requirements were found to improve by ∼26%, ∼66% and ∼56%, respectively, with good arc-stability.

This study explores the numerical analysis of effective stress and distortion (dimensional variations) in bulk deposited structures of Inconel 625 alloy with seven different deposition strategies using wire arc additive manufacturing (WAAM) process. Due to the challenges in detecting in-situ stress changes during bulk deposition, numerical analysis is employed to approximate stress distribution. The goal is to investigate stress and distortion (dimensional variations) in the build direction (BD), longitudinal and transverse directions, and understand their impact on anisotropy and asymmetry. The findings reveal distinct patterns in effective stress, with initial decrease in bottom, followed by a gradual increase at the middle and rapid increase thereafter, regardless of deposition strategies. Parallel and contour deposition strategies exhibit lower effective stress compared to spiral strategies. Distortion (dimensional variations) along the BD increases with height, and parallel strategies result in higher distortion. The parallel strategies show increasing distortion from one edge to the other, while spiral and contour strategies lead to high distortion at the center. The parallel and contour deposition strategies exhibit higher compressive stress at the bottom and middle compared to the spiral strategies. Anisotropy analysis indicates higher stress anisotropy in parallel and contour patterns, but lower distortion anisotropy compared to spiral patterns. Empirical equations are developed to understand the relationship between stress, distortion (dimensional variations) and hardness. The study suggests that higher effective stress can adversely affect material yielding behavior. This study undertakes a comparison between FEA and analytical model which reveals a close alignment in the residual stress distributions in the build direction.

Machining is extensively used for producing functional parts in various industries such as aerospace, automotive, energy, etc. There is a growing demand for improved part quality and performance at lower costs from increasingly difficult-to-machine materials. Whilst modern machine tools are equipped with sensors for closed loop control of their axes’ movements and position, they provide minimal information regarding the cutting performance and tool condition. The integration of additional sensors into cutting tools, machine tools and/or their components can provide an insight into the machining performance. It also provides an opportunity to improve the machining process and reduce the need for post-process inspection and rework. This paper presents a comprehensive analysis of various sensors utilised for in-process and on-machine measurement and monitoring of machining performance parameters such as cutting forces, vibrations, tool wear, surface integrity, etc. Data transfer and communication methods, as well as power supply options for sensor-integrated systems are also investigated. Sensor integrated machining systems can potentially improve machining performance and part quality by early detection of errors and damages, maximising tool usage and preventing machining and tool wear induced damages. A combination of sensor data collection and intelligent sensor signal processing can further increase the capabilities of sensor integrated systems from process monitoring to active process control.