Advances in Manufacturing最新文献

Accurate intelligent reasoning systems are vital for intelligent manufacturing. In this study, a new intelligent reasoning system was developed for milling processes to accurately predict tool wear and dynamically optimize machining parameters. The developed system consists of a self-learning algorithm with an improved particle swarm optimization (IPSO) learning algorithm, prediction model determined by an improved case-based reasoning (ICBR) method, and optimization model containing an improved adaptive neural fuzzy inference system (IANFIS) and IPSO. Experimental results showed that the IPSO algorithm exhibited the best global convergence performance. The ICBR method was observed to have a better performance in predicting tool wear than standard CBR methods. The IANFIS model, in combination with IPSO, enabled the optimization of multiple objectives, thus generating optimal milling parameters. This paper offers a practical approach to developing accurate intelligent reasoning systems for sustainable and intelligent manufacturing.

In recent years, green concepts have been integrated into the product iterative design in the manufacturing field to address global competition and sustainability issues. However, previous efforts for green material optimal selection disregarded the interaction and fusion among physical entities, virtual models, and users, resulting in distortions and inaccuracies among user, physical entity, and virtual model such as inconsistency among the expected value, predicted simulation value, and actual performance value of evaluation indices. Therefore, this study proposes a digital twin-driven green material optimal selection and evolution method for product iterative design. Firstly, a novel framework is proposed. Subsequently, an analysis is carried out from six perspectives: the digital twin model construction for green material optimal selection, evolution mechanism of the digital twin model, multi-objective prediction and optimization, algorithm design, decision-making, and product function verification. Finally, taking the material selection of a shared bicycle frame as an example, the proposed method was verified by the prediction and iterative optimization of the carbon emission index.

This paper presents a predictive defect detection method for prototype additive manufacturing (AM) based on multilayer susceptibility discrimination (MSD). Most current methods are significantly limited by merely captured images, disregarding the differences between layer-by-layer manufacturing approaches, without combining transcendental knowledge. The visible parts, originating from the prototype of conceptual design, are determined based on spherical flipping and convex hull theory, on the basis of which theoretical template image (TTI) is rendered according to photorealistic technology. In addition, to jointly consider the differences in AM processes, the finite element method (FEM) of transient thermal-structure coupled analysis was conducted to probe susceptible regions where defects appeared with a higher possibility. Driven by prior knowledge acquired from the FEM analysis, the MSD with an adaptive threshold, which discriminated the sensitivity and susceptibility of each layer, was implemented to determine defects. The anomalous regions were detected and refined by superimposing multiple-layer anomalous regions and comparing the structural features extracted using the Chan-Vese (CV) model. A physical experiment was performed via digital light processing (DLP) with photosensitive resin of a non-faceted scaled V-shaped engine block prototype with cylindrical holes using a non-contact profilometer. This MSD method is practical for detecting defects and is valuable for a deeper exploration of barely visible impact damage (BVID), thereby reducing the defect of prototypical mechanical parts in engineering machinery or process equipment via intellectualized machine vision.

Deformation allocation is an important factor that affects 720° curling forming from copper-coated steel strips to double-walled brazed tubes (DWBTs). In this study, four schemes of deformation allocation, considering different weights of the total feed distance, are proposed, and a 3D finite element (FE) model of the multi-pass roll forming process for DWBT is developed and verified to investigate the cross-sectional evolution and deformation features. The results show the following. (i) In the 720° curling forming process from the steel strip into double-walled tubes, the curvature of the formed circular arc initially increases and then remains stable with roll forming, and the inner and outer tubes of the DWBT are formed in the third and fifth forming passes. Size forming can eliminate the gap between the double walls and improve the overall roundness. (ii) For different deformation allocations, the cross-sectional profiles of the roll-formed parts exhibit a discrepancy, and the deformation amount varies with the roll-forming process. The deformation amount in Scheme three is the maximum, and the cross-sectional profile deviates significantly from the ideal shape and fails to form a DWBT, which indicates that the deformation allocation is unsuitable. (iii) The roundness of the outer tube is better than that of the inner tube. Therefore, the roundness of the inner tube is the key to restricting the forming accuracy of the DWBT. Compared with Schemes one and two, Scheme four with a linear allocation of the total feed distance exhibits the best roundness, and the deformation allocation is reasonable; i.e., when the contact points between the rollers and steel strip are in a straight line, the roundness of the DWBT is in good agreement with the ideal condition.

Distortion during the forging or machining processes of a blade causes problems in subsequent manufacturing. This paper proposes an alternative multipoint correction method integrated with blade measurement, determination of correcting parameters, and adjustment of the correcting die. An iterative algorithm for determining the correcting parameters is proposed. Measuring equipment combining a laser displacement sensor with multipoint flexible support is manufactured to measure the blade shape. Multipoint correcting equipment with an adaptive lower die and rapid adjustment is manufactured, and software is developed for data analysis and equipment control. The correction experiment for a rough-machined steam-turbine blade indicates that the correcting parameters can be determined after one modification based on numerical simulation, and that a rough blade that meets the allowance for finish machining can be obtained using the determined correction parameters.

Abrasive waterjet (AWJ) is widely applied in 2D machining as it offers high machining efficiency and low machining cost. However, machining a 3D surface, especially for a small curvature radius freeform surface (SCRFS), results in over-erosion of the corner, and has been one of the greatest issues of AWJ. To solve this problem, a local smoothing algorithm for SCRFS is developed by the junction of two linear segments at the corner by inserting cubic second-order B-spline to smooth the nozzle path and posture under the setting tolerance error, which is aimed to avoid over-erosion due to the change in dwell time. Analytical solutions of the smooth corner position and orientation of the nozzle path are obtained by evaluating a synchronization algorithm. According to the set tolerance error of the nozzle position and orientation, the interpolation of the smooth path of the corner meets the constraint conditions of the linear feed drive. Path simulation and experimental results show that the proposed method is validated by the experimental results and has been applied to the integral blisk machining of an aero-engine.

The second-generation high-temperature superconductor tape (2G-HTS, also known as a coated conductor) based on REBaCuO (REBa₂Cu₃O_7–δ) exhibits high current density and potential cost-effective price/performance, compared with conventional superconducting materials. Using commercial 2G-HTS tapes, more than a dozen cable vendors had been manufacturing REBCO cables, such as the latest kilometer-class REBCO cable, which was incorporated into a civil grid on December 2021, as part of the record-breaking 35-kV-voltage superconductor cable demonstration project in downtown Shanghai. This paper describes the development of HTS-coated conductors, then outlines the various technological routes for their preparation, reviews the artificial flux pinning of coated conductors, and finally summarizes the technological breakthroughs, the latest research advances, and provides an outlook on their application prospects.

The heat generated and accumulated on the machined surface of an Inconel 718 workpiece causes thermal damage during the cutting process. Surface-active media with high thermal conductivity coated on the workpiece to be machined may have the potential to reduce the generation of cutting heat. In this study, a theoretical model for predicting the instantaneous machined surface temperature field is proposed for surface-active thermal conductive medium (SACM)-assisted cutting based on the finite element and Fourier heat transfer theories. Orthogonal cutting experiments were performed to verify the results predicted using the proposed surface-temperature field model. Three SACMs with various thermal conductivities were used to coat Inconel 718 surface to be machined. Thermocouples embedded into the workpiece were used to measure the cutting temperature at different points on the machined workpiece surface during the cutting process. The experimental results were in agreement with the predicted temperatures, and the maximum error between the experimental results and predicted temperatures was approximately 9.5%. The cutting temperature on the machined surface decreased with an increase in the thermal conductivity of the SACM. The graphene SACM with high thermal conductivity can effectively reduce the temperature from 542 °C to 402 °C, which corresponds to a reduction of approximately 26%. The temperature reduction due to SACM decreases with an increase in the distance between the temperature prediction point and machined workpiece surface. In conclusion, the cutting temperatures on the machined workpiece surface can be reduced by coating with SACM.

Understanding the fracture behavior of fused silica in contact sliding is important to the fabrication of damage-free optics. This study develops an analytical method to characterize the stress field in fused silica under contact sliding by extending the embedded center of dilation (ECD) model and considering the depth of yield region. The effects of densification on the stress fields were considered by scratch volume analysis and finite element analysis. Key mechanisms, such as crack initiation and morphology evolution were comprehensively investigated by analyzing the predicted stress fields and principal stress trajectories. The predictions were validated by Berkovich scratching experiment. It was found that partial conical, median and lateral cracks could emerge in the loading stage of the contact sliding, but radial and lateral cracks could be initiated during unloading. It was also found that the partial conical crack had the lowest initiation load. The intersection of long lateral cracks makes the material removal greater.

Robotic autonomous operating systems in global n40avigation satellite system (GNSS)-denied agricultural environments (green houses, feeding farms, and under canopy) have recently become a research hotspot. 3D light detection and ranging (LiDAR) locates the robot depending on environment and has become a popular perception sensor to navigate agricultural robots. A rapid development methodology of a 3D LiDAR-based navigation system for agricultural robots is proposed in this study, which includes: (i) individual plant clustering and its location estimation method (improved Euclidean clustering algorithm); (ii) robot path planning and tracking control method (Lyapunov direct method); (iii) construction of a robot-LiDAR-plant unified virtual simulation environment (combination use of Gazebo and SolidWorks); and (vi) evaluating the accuracy of the navigation system (triple evaluation: virtual simulation test, physical simulation test, and field test). Applying the proposed methodology, a navigation system for a grape field operation robot has been developed. The virtual simulation test, physical simulation test with GNSS as ground truth, and field test with path tracer showed that the robot could travel along the planned path quickly and smoothly. The maximum and mean absolute errors of path tracking are 2.72 cm, 1.02 cm; 3.12 cm, 1.31 cm, respectively, which meet the accuracy requirements of field operations, establishing the effectiveness of the proposed methodology. The proposed methodology has good scalability and can be implemented in a wide variety of field robot, which is promising to shorten the development cycle of agricultural robot navigation system working in GNSS-denied environment.