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In industrial robotic arm gripping operations within disordered environments, the loss of physical information on the object's surface is often caused by changes such as varying lighting conditions, weak surface textures, and sensor noise. This leads to inaccurate object detection and pose estimation information. A method for industrial object pose estimation using point cloud data is proposed to improve pose estimation accuracy. During the feature extraction process, both global and local information are captured by integrating the appearance features of RGB images with the geometric features of point clouds. Integrating semantic information with instance features effectively distinguishes instances of similar objects. The fusion of depth information and RGB color channels enriches spatial context and structure. A cross-entropy loss function is employed for multi-class target classification, and a discriminative loss function enables instance segmentation. A novel point cloud registration method is also introduced to address re-projection errors when mapping 3D keypoints to 2D planes. This method utilizes 3D geometric information, extracting edge features using point cloud curvature and normal vectors, and registers them with models to obtain accurate pose information. Experimental results demonstrate that the proposed method is effective and superior on the LineMod and YCB-Video datasets. Finally, objects are grasped by deploying a robotic arm on the grasping platform. [ABSTRACT FROM AUTHOR]

Steam turbine blades may crack, break, or suffer other failures due to high temperatures, high pressures, and high-speed rotation, which seriously threatens the safety and reliability of the equipment. The signal characteristics of different fault types are slightly different, making it difficult to accurately classify the faults of rotating blades directly through vibration signals. This method combines a one-dimensional convolutional neural network (1DCNN) and a channel attention mechanism (CAM). 1DCNN can effectively extract local features of time series data, while CAM assigns different weights to each channel to highlight key features. To further enhance the efficacy of feature extraction and classification accuracy, a projection head is introduced in this paper to systematically map all sample features into a normalized space, thereby improving the model's capacity to distinguish between distinct fault types. Finally, through the optimization of a supervised contrastive learning (SCL) strategy, the model can better capture the subtle differences between different fault types. Experimental results show that the proposed method has an accuracy of 99.61%, 97.48%, and 96.22% in the classification task of multiple crack fault types at three speeds, which is significantly better than Multilayer Perceptron (MLP), Residual Network (ResNet), Momentum Contrast (MoCo), and Transformer methods. [ABSTRACT FROM AUTHOR]

With the continuous development of the global logistics industry, cold chain transportation and joint distribution, as critical strategies in supply chain management, are gradually becoming key means to ensure the safe transportation of perishable goods, pharmaceuticals, and other temperature-sensitive commodities. The present study is dedicated to an in-depth exploration of cold chain logistics and joint distribution, with a particular focus on a review of fresh food logistics modes, aiming to comprehensively understand their operational modes, advantages, challenges, and future development trends. The present study elucidates the basic concepts of fresh food logistics and underscores its significance in supply chain management. Through comparative analysis of different operational modes, it reveals their advantages in enhancing efficiency, reducing costs, and mitigating environmental impacts. The present study focuses on the operational mode of joint distribution, discussing its application in cold chain logistics and its differences from traditional logistics modes. Through case studies and empirical analysis, it evaluates the impact of joint distribution on logistics efficiency and costs, as well as its potential to enhance transportation efficiency and reduce carbon emissions. Lastly, the present study provides an outlook on the future development trends of cold chain logistics and joint distribution, discussing the influences of technological innovation, policy support, and industry collaboration and offering recommendations and prospects to drive the sustained development of the industry. Through a comprehensive summary of fresh food logistics, cold chain logistics operational modes, and joint distribution operational modes, this paper aims to provide in-depth theoretical support and practical guidance for related research and practices. [ABSTRACT FROM AUTHOR]

A sulfur-containing polyphosphonate compound, polysulfonyldiphenylene phenylphosphonate (PSPPP), was prepared based on diphenylphosphine and bisphenol S, and applied to flame retarded polyethylene terephthalate (PET). The flame retardancy and thermal stability of PSPPP/PET composites were investigated by limiting oxygen index (LOI), vertical burning test (UL-94), cone calorimeter and thermogravimetric analysis (TGA). LOI value increased from 20.5% for pure PET to 29.2% for flame retardant PET with 8 wt.% PSPPP, and 8%PSPPP/PET passed UL-94 V-0 rating. The cone calorimeter test displayed that PSPPP not only inhibited the maximum combustion strength of PET composites but also suppressed the smoke release. TGA results indicated that PSPPP significantly enhanced the char yield of composites and the thermal stability of residues at higher temperature. The flame retardant modes of action of PSPPP were confirmed by experiments using TGA-Fourier transform infrared (TGA-FTIR), pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS), Hot-Stage FTIR, and scanning electron microscope (SEM). PSPPP played a role of flame retardant in condensed phase and gas phase. During combustion, PSPPP continuously released phosphorus-oxygen-free radicals with quenching effect, thus playing the gas phase flame retardant effect. On the other hand, the transesterification reactions between PSPPP and PET promoted the formation of dense carbon layer and led to high barrier effect. [ABSTRACT FROM AUTHOR]

In cloud manufacturing environments, the scheduling of multi-user manufacturing tasks often fails to consider the impact of service supply on resource allocation. This study addresses this gap by proposing a bi-objective multi-user multi-task scheduling model aimed at simultaneously minimising workload and maximising customer satisfaction. To accurately capture customer satisfaction, a novel comprehensive rating index is introduced, integrating the actual completion cost, time, and processing quality against customer expectations. Furthermore, vehicle constraints are incorporated into the model to accommodate potential delays in transport vehicle availability, thereby enhancing its alignment with real-world manufacturing settings. The proposed mathematical model is solved using an improved three-stage genetic algorithm, which integrates the k-means algorithm and a real-time sequence scheduling strategy to optimise solution quality. Validation against alternative algorithms across various case scales demonstrates the efficacy of the approach in providing practical scheduling solutions for real-case scenarios. [ABSTRACT FROM AUTHOR]

In the current intelligent manufacturing scenario, single-mode perception limits the accuracy and safety of the human-robot collaboration process, and cannot adapt to the assembly operation requirements of robots in complex industrial environments. To solve these problems, this paper proposes a Human-Robot Collaboration (HRC) framework for a dual-robot intelligent assembly system based on multimodal perception. This framework aims to provide multimodal information interaction for robot control through gesture perception, speech perception, human body perception, and visual perception. To verify the effectiveness of this framework, it was applied to the assembly scene of the integrally shrouded blade-rotor system. Experiments show that the multimodal perception dual-robot intelligent assembly system can better realize the HRC assembly of the integrally shrouded blade and improve the intelligence of the assembly process. It shows that the framework can promote robots to flexibly and accurately perceive information among people, robots, and objects to complete intelligent assembly. The multimodal information interaction effectively improves the operational robustness of the dual-robot intelligent assembly system in complex industrial environments and complex tasks. [ABSTRACT FROM AUTHOR]

Aiming to address problems such as low sampling success rate and long computation time in the motion planning of a dual-arm cooperative system with multiple constraints, this paper proposes an Informed-Bi-Quick RRT* algorithm based on offline sampling. First, in the process of pre-sampling, the new algorithm relaxes the approximation of constrained manifolds by introducing the idea of incremental construction, and it incorporates the stochastic gradient descent method to replace global random sampling with local random sampling, which enriches the data set and shortens the offline sampling time of the data set. Second, the new algorithm improves the original Quick-RRT* algorithm by combining the two-tree idea and the multi-target bias expansion strategy, and it improves the adaptability of the algorithm to different obstacle environments. In addition, the loosely constrained motion and tightly constrained motion in the two-arm cooperative system are analyzed, and the adaptive planning of the two-arm trajectory in different motions is described in detail. In this paper, the two-arm cooperative model constructed with UR5 and UR10 robot arms is studied, and the ability of the proposed algorithm to deal with multiple constraints is verified by simulating assembly and handling tasks. The experimental results show that compared with other methods, the proposed algorithm has obvious advantages in path quality and planning efficiency. [ABSTRACT FROM AUTHOR]

In flexible job shop scheduling problem (FJSP), the collision of bidirectional rail guided vehicles (RGVs) directly affects RGVs scheduling, and it is closely coupled with the allocation of production equipment, which directly affects the production efficiency. In this problem, taking minimizing the maximum completion time of RGVs and minimizing the maximum completion time of products as multi-objectives a dual-resource integrated scheduling model of production equipment and RGVs considering conflict-free routing problem (CFRP) is proposed. To solve the model, a multi-objective improved discrete grey wolf optimizer (MOID-GWO) is designed. Further, the performance of popular multi-objective evolutionary algorithms (MOEAs) such as NSGA-Ⅱ, SPEA2 and MOPSO are selected for comparative test. The results show that, among 42 instances of different scales designed, 37, 34 and 28 instances in MOID-GWO are superior to the comparison algorithms in metrics of generational distance (GD), inverted GD (IGD) and Spread, respectively. Moreover, in metric of Convergence and Diversity (CD), the Pareto frontier (PF) obtained by MOID-GWO is closer to the optimal solution. Finally, taking the production process of a construction machinery equipment component as an example, the validity and feasibility of the model and algorithm are verified. [ABSTRACT FROM AUTHOR]

In the realm of industrial robotics, there is a growing challenge in simplifying human–robot collaboration (HRC), particularly in complex settings. The demand for more intuitive teleoperation systems is on the rise. However, optimizing robot control interfaces and streamlining teleoperation remains a formidable task due to the need for operators to possess specialized knowledge and the limitations of traditional methods regarding operational space and time constraints. This study addresses these issues by introducing a virtual reality (VR) HRC system with five-dimensional capabilities. Key advantages of our approach include: (1) real-time observation of robot work, whereby operators can seamlessly monitor the robot's real-time work environment and motion during teleoperation; (2) leveraging VR device capabilities, whereby the strengths of VR devices are harnessed to simplify robot motion control, significantly reducing the learning time for operators; and (3) adaptability across platforms and environments: our system effortlessly adapts to various platforms and working conditions, ensuring versatility across different terminals and scenarios. This system represents a significant advancement in addressing the challenges of HRC, offering improved teleoperation, simplified control, and enhanced accessibility, particularly for operators with limited prior exposure to robot operation. It elevates the overall HRC experience in complex scenarios. [ABSTRACT FROM AUTHOR]

Modeling errors and external disturbances have significant impacts on the control accuracy of robotic arm trajectory tracking. To address this issue, this paper proposes a novel method, the neural network terminal sliding mode control (ALSSA-RBFTSM), which combines fast nonsingular terminal sliding mode (FNTSM) control, radial basis function (RBF) neural network, and an improved salp swarm algorithm (ALSSA). This method effectively enhances the trajectory tracking accuracy of robotic arms under the influence of uncertain factors. Firstly, the fast nonsingular terminal sliding surface is utilized to enhance the convergence speed of the system and achieve finite-time convergence. Building upon this, a novel multi-power reaching law is proposed to reduce system chattering. Secondly, the RBF neural network is utilized to estimate and compensate for modeling errors and external disturbances. Then, an improved salp swarm algorithm is proposed to optimize the parameters of the controller. Finally, the stability of the control system is demonstrated using the Lyapunov theorem. Simulation and experimental results demonstrate that the proposed ALSSA-RBFTSM algorithm exhibits superior robustness and trajectory tracking performance compared to the global fast terminal sliding mode (GFTSM) algorithm and the RBF neural network fast nonsingular terminal sliding mode (RBF-FNTSM) algorithm. [ABSTRACT FROM AUTHOR]

Six-axis industrial assembly robotic arms are pivotal in the manufacturing sector, playing a crucial role in the production line. The IPQ-RRT* connect motion planning algorithm for the robotic arm is proposed to improve the assembly process by reducing the time of motion planning and improving the assembly efficiency. The new IPQ-RRT* connect algorithm improves the original PQ-RRT* algorithm applied to UAVs in two dimensions by adding a node-greedy bidirectional scaling strategy. An obstacle detection range is set on the node-greedy bidirectional scaling strategy, in which the existence of obstacles is judged, and different sampling strategies are used according to the judgment results to get rid of obstacles faster, while bidirectional sampling can further improve the operation efficiency of the algorithm. In addition, effective collision detection is realized by combining the hierarchical wraparound box method. Finally, the Bezier curve is utilized to smooth the trajectory of the assembly robotic arm, which improves the trajectory quality while ensuring that the assembly robotic arm does not collide with obstacles. This paper takes the actual assembly process of an intelligent assembly platform as an example and proves the feasibility and effectiveness of the algorithm through simulation experiments and real I5 assembly robotic arm experiments. [ABSTRACT FROM AUTHOR]

The nanofiltration (NF) membrane technology has attracted considerable attention for the rejection removal of various salts. However, the practical application of this membrane separation process has been severely retarded due to the ineffective rejection of monovalent ions (such as nitrate and chloride), undesirable filtration flux, and insufficient disposal of the concentrated solution. In this work, three polyethersulfone‐type NF membranes were fabricated and their morphologies, functional groups, chemical components, wettabilities, chargeabilities, and rejection molecular weights were characterized. Among them, the membrane of NF_M3 bearing sulfonic acid group (SO3H) shows the desirable rejection efficiency of nitrate (90.32%), acceptable solution filtration flux (10.15 L m−2 h−1 at 0.6 MPa), and the decent pure water permeation flux (50.8 L m−2 h−1 at 0.6 MPa). The introduction of SO3H can significantly enhance the performances of NF_M3 membrane in hydrophilicity, chargeability, anti‐fouling, and the oxidation resistance. Promisingly, the concentrated nitrate was ingeniously recycled for the electrochemical intercalation of flake graphite to prepare expandable graphite, and the obtained expanded graphite has an acceptable expanded volume (243 mL g−1 via the microwave expansion process), thereby achieving the resource utilization of NF concentrated solution. [ABSTRACT FROM AUTHOR]

Based on the problem of shroud gap and shroud friction having impact on the blade collision vibration, a three-blade dynamic analysis model considering shroud friction and asymmetric gap is established in the present work. In order to study the effect of asymmetric gap and shroud friction coefficient on the vibration of the twisted shrouded blade in practice. The differential equations of shroud oblique collision between the twisted shrouded blade and adjacent blades were established, and a nonlinear Hertz contact force and an exponentially decaying friction model were used to describe the shroud contact collision force and friction, respectively. Numerical simulation and experiment are used to verify the vibration response of the blade under different gaps. The results show that the shroud movement under the asymmetric gap is more complicated than symmetric gap. The presence of shroud friction causes the passive blades to enter a cyclic motion. And shroud friction coefficient increases will decrease the amplitude of the blade. [ABSTRACT FROM AUTHOR]