The objective of this research is to predict the solder joint’s fillet profile before its formation. Solder joints are crucial for the structural and operational reliability of electronic assemblies, yet their integrity can be compromised by defects such as cold joints, voids, or insufficient solder. Traditional physics-based simulations attempt to model these phenomena but often fall short due to

Additive manufacturing (AM) technologies have undergone significant advancements through the integration of cooperative robotics additive manufacturing (C-RAAM) platforms. By deploying AM processes on the end effectors of multiple robotic arms, not only are traditional constraints such as limited build volumes circumvented, but systems also achieve accelerated fabrication speeds, cooperative sensing

In the demanding sectors of shipbuilding and aerospace, the assembly of large thin-walled components is a pivotal process, challenged by the need to minimize part deformation and assembly gaps. This study introduces an innovative flexible fixture system designed to enhance assembly accuracy by optimizing fixture layouts using the Tabu Search Algorithm (TSA). The proposed system not only adapts to various

In limited visibility human-machine environments, there has been little discussion on hand motion parameter extraction, behavioral intention data analysis, and the effectiveness of 3D assembly instructions. To address this issue, we developed a mixed reality system for fully occluded gesture recognition (Fog-MR), which supports the extraction of complete hand motion models, the determination of a directional

The convergence of Cloud Manufacturing and Cyber-Physical Systems (CPS) presents an opportunity worth exploring. This paper looks into integrating these two concepts by utilising the OPC Unified Architecture (OPC UA) as a key communication protocol. Following a critical review of the relevant concepts, the authors propose a conceptual hybrid architecture that relies on OPC UA to facilitate seamless

The prediction of chatter-free machining parameters suffers from inaccuracies in dynamic milling model inputs and simplification in milling process modeling, which may lead to a significant mismatch between the predicted stability boundary of the mathematical model and actual physical experiments. This study proposes a novel stability analysis method for milling operations based on a surrogate model

In this paper, we present a survey on recent trends in robotics and artificial intelligence in the furniture industry. We first introduce the state-of-the-art applications of traditional and collaborative industrial robots in this field, with a particular focus on finishing, painting, and assembly operations. Then, the main uses of data management and artificial intelligence are described. Finally

Recent rapid developments of dexterous robotic hands have greatly enhanced the manipulative capabilities of robots, enabling them to perform industrial tasks in human-like dexterity. These advancements not only enhance operational efficiency but also liberate human operators from monotonous tasks, allowing them to focus on creative and intellectually demanding. Despite the considerable attention robotic

This paper addresses the challenge of integrated optimization for storage space allocation and crane scheduling in automated storage and retrieval systems. The problem encompasses tasks such as assigning storage/retrieval requests, allocating storage spaces, and planning crane routes within each operation cycle. To tackle this, we introduce a multi-layer adaptive length coding method to effectively

Robot automatic peg-in-hole assembly is a challenging task. Human perception-decision-operation skills play an irreplaceable role in precise assembly. In this paper, human assembly skills are modeled as a multi-level Markov decision process, and a multi-level imitation model is proposed to learn human assembly skills from demonstrations. Specifically, to learn human skills of identifying assembly phases

This paper explores the issue of protective film removal in the hand layup process for composite parts production. The hand layup process, involving the assembly of prepreg plies onto a mold, is a skill-intensive task performed by multiple expert workers. A significant limitation of this method is its low repeatability, which impacts both the consistency and quality of the final product. The current

In the context of human-centric smart manufacturing, human-robot collaboration (HRC) systems leverage the strengths of both humans and machines to achieve more flexible and efficient manufacturing. In particular, estimating and monitoring human motion status determines when and how the robots cooperate. However, the presence of occlusion in industrial settings seriously affects the performance of human

In modern organic light-emitting diode (OLED) manufacturing systems, scheduling is a key decision-making problem to improve productivity. In particular, the scheduling of evaporation and encapsulation stages has been confronted with complicated constraints such as job-splitting property, preventive maintenance, machine eligibility, family setups, and heterogeneous release time of jobs. To efficiently

Robotic machining has been increasingly applied in intelligent manufacturing production lines. Compared with the traditional machine tools, commissioning for robotic machining system (RMS) is particularly important due to the low accuracy of industrial robots (IRs). Traditional site commissioning has large workload and is difficult to handle the multi-source errors. Since digital twin (DT) provides

Triangular mesh representation is extensively utilized in geometric design and reverse engineering. However, in the realm of high quality CNC machining, there is a notable transition from mesh to continuous surface representation for workpieces. This paper presents a novel approach to address this shift, proposing a high-precision and efficient path generation method of ball-end milling specifically

Robotic ball-end milling presents advantages such as a broad workspace, cost-effectiveness, and integration with vision/force sensing, making it a promising method in machinery manufacturing. However, its low stiffness leads to deformation error that seriously affects part profile accuracy. Reducing the deformation error is an effective method to improve the machining accuracy of robotic milling. However

Mobile manipulators are increasingly deployed in industrial settings, such as material handling and workpiece loading, where they must safely interact with humans while efficiently completing tasks. Existing motion planning methods for mobile manipulators often struggle to ensure both safety and efficiency in dynamic human-robot interaction environments. This paper proposes a Safety Posture Field framework

The evolution of manufacturing towards intelligent and digital processes requires innovation in machining quality control. While current research primarily addresses single-scale quality control, it overlooks comprehensive multi-scale product quality characterization. Digital twin technology emerges as a potential solution. This review examines digital twin applications in machining quality control

This paper proposes a novel NER framework, leveraging the advanced capabilities of Large Language Models (LLMs), to address the limitations of manually defined taxonomy. Our framework integrates the expert knowledge internalized in both academic materials and LLMs through retrieval-augmented generation (RAG) to automatically customize taxonomies for specific manufacturing processes and adopts two distinct

Due to the structural resemblance of redundant dual-arm robots to human arms, they are widely employed to replace humans in open operational environments. Addressing safety concerns related to the autonomous operations of redundant dual-arm robots in open environments, this paper proposes a real-time collision avoidance method. Firstly, an avoidance direction adjustment algorithm is designed based

Tool wear monitoring (TWM) is essential for enhancing the machining accuracy of intelligent manufacturing systems and ensuring the consistency and reliability of products. The complex and dynamic processing environment demands higher real-time monitoring and generalization ability of TWM. Traditional data-driven models lack guided training in physical processes and are limited by the amount of samples

Mixed reality remote collaboration assembly is a type of computer-supported collaborative assembly work that uses mixed reality technology to enable spatial information and collaboration status sharing among geographically distributed collaborators, including remote experts and local users. However, due to the abundance of mixed virtual and real-world information in the MR space and the limitations

Aero-engine nacelle acoustic liners are complex curved surface subassemblies with tens of thousands of dense acoustic holes for noise reduction. Traditional robotic drilling systems with a single spindle and conventional teaching programming cannot meet the high-quality and high-efficiency drilling requirements for nacelle acoustic liners. This paper developed a novel robotic multi-spindle drilling

Directed Energy Deposition (DED) is a free-form metal additive manufacturing process characterized as toolless, flexible, and energy-efficient compared to traditional processes. However, it is a complex system with a highly dynamic nature that presents challenges for modeling and optimization due to its multiphysics and multiscale characteristics. Additionally, multiple factors such as different machine

In the coming decades, robotized mobile machining equipment (RMME) is possible to evolve as a new branch of machine tools due to its exceptional flexibility. The frequency response function (FRF) serves as a theoretical foundation in controlling the vibration deformations that significantly limit the material removal efficiency of RMME. Model updating, aimed at minimizing errors between the theoretical

Variable impedance control (VIC) endows robots with the ability to adjust their compliance, enhancing safety and adaptability in contact-rich tasks. However, determining suitable variable impedance parameters for specific tasks remains challenging. To address this challenge, this paper proposes an imitation learning-based VIC policy that employs observations integrated with RGBD and force/torque (F/T)

The robotic manipulation of deformable linear objects (DLOs), such as cables, is a valuable yet complex skill. In particular, to realize tasks like cable routing and wire harness assembly, it is required that two robotic arms, grasping the ends of a DLO, move it from an initial shape to a final one where cable assembly can be performed. The manipulation must be performed following a collision-free

In robotic and automation industry, micromanipulation and micromanipulator have recognized significant advancements due to they are involved in handling of micro-sized parts from a few to hundreds of micrometers. In order to perform such precise grasping tasks, compliant grippers have been increasingly developed, and they have critically significant contributions in the high precision micromanipulation

The revolutionary advances in integrated components in current automotive industry have led to a sharply rising demand for aluminum alloy castings. Targeted quality inspection is thus proposed for components manufacturers to achieve high responsiveness and low operational cost. This suggests casting machine manufacturers to integrate advanced quality prediction functions into the next generation of

Digital twin tools for additive manufacturing (AM) are constrained by the underlying representations of component geometry that are currently in wide use. Mesh, voxel, and parametric surface representations require numerous conversions to intermediate representations at multiple points throughout the processing chain. Each conversion introduces additional error in the geometric representation and complicates

Trajectory accuracy, a crucial metric in assessing the dynamic performance of grinding robots, is influenced by the uncertain movement of the tool center point, directly impacting the surface quality of processed workpieces. This article introduces an innovative method for compensating trajectory errors. Initially, a strategy for error compensation is derived using differential kinematics theory. Subsequently

The joint deflection of robots in machining degrades product accuracy. Compliance error compensation has been investigated to reduce the static deflection of robotic machining. The challenge in compliance error compensation is accurately measuring the deflection or cutting force. External sensors have been used to measure them in robotic machining, but it is not practical. The authors proposed a nonlinear

Monitoring tool breakage during computer numerical control machining is essential to ensure machining quality and equipment safety. In consideration of the low cost in long-term use and the non-invasiveness to workspace, using servo signals of machine tools to monitor tool breakage has been viewed as the solution that has great potential to be applied in real industry. However, because machine tool

The present study aims at exploring the effect of communicating robots’ intent through visual cues, to the human on a complex human-robot collaborative task. Specifically, it aims to investigate (i) whether the use of such “anticipatory cues” will have a positive effect on task efficiency, human safety and collaborating fluency, (ii) the degree of this effect with varying robots’ speed and (iii) whether

Adaptive allocation of the machining allowance is the crucial factor in ensuring the machining accuracy of complex parts. In this work, we present a multi-objective constraint registration method. First, an improved point cloud segmentation method is developed by combining point search and region data expansion algorithms. Afterward, the machining allowance is accurately calculated by using statistical

Trajectory planning is crucial in the motion planning of robots, where finding the time-optimal path parameterization (TOPP) of a given path subject to kinodynamic constraints is an important component of trajectory planning. The tangential discontinuity at the intersection of continuous line segments limits the speed of trajectory planning and can easily cause jitter and over-constraint phenomena

Nowadays, Industry 5.0 starts to gain attention, which advocates that intelligent manufacturing should adequately consider the roles and needs of humans. In this context, how to enhance human capabilities or even liberate humans from the processes of perception, learning, decision-making, and execution has been one of the key issues to be addressed in intelligent manufacturing. Large language models

Carbon fiber reinforced polymers (CFRP) have significant applications in aerospace and automotive manufacturing. However, due to the complexity of CFRP structures, manufacturing defects are challenging to avoid and even affect the mechanical properties. Timely detection and repair are essential to ensure product quality. In this study, we propose a robotized framework for real-time detection and in-situ

In the field of robotic polishing, achieving uniform material removal typically involves addressing the issue of constant contact force control. However, multi-source external disturbances in the polishing scenarios of complex workpiece surfaces can severely affect the robot’s force control accuracy. To enhance the responsiveness and disturbance rejection capabilities of robots in the compliant polishing

Path smoothing and trajectory planning are universally applied in computer-numerical-control (CNC) machining to avoid natural discontinuity of tangency and curvature at the junctions of G01 blocks. However, most existing methods primarily focus on path-centric indicators that consider the toolpath as a continuous curve, such as contour error and manufacturing efficiency, neglecting the global machining

Robotic machining could provide a solution for removing supports from metal additive manufactured workpieces, replacing labor-intensive work. However, the robot’s intrinsic weaknesses of low positioning accuracy and structural rigidity primarily restrict its applications. Improving the accuracy of robotic machining remains an unresolved issue. A mixed solution is proposed, in which a portable CNC machine

Visual recognition of weld beads is essential for post-weld robotic grinding. The recognition of thin-walled weld bead boundary, especially the backside boundary, remains challenging due to the diverse features such as debris, misalignment, and deformation. Based on point cloud from a laser scanner, we present a robust and accurate backside boundary recognition method for girth weld beads of thin-walled

The process design intent is the concentration of the technologists’ design cognitive process which contains the experiential knowledge and skills. It can reproduce technologists’ design thinking process in process design and provides guidance and interpretability for the generation of process results. The machining process route, as a core component of a part's entire manufacturing process, contains

Human–robot collaborative polishing can integrate the capabilities of humans and automation to deal with complex polishing tasks. Traditional impedance-control-based human–robot collaboration (HRC) requires operators to physically interact with robots for a good polishing performance, which brings unsafety to operators. To address this issue, a corrective shared control architecture using haptic feedback

Generating model-free grasps in complex scattered scenes remains a challenging task. Most current methods adopt PointNet++ as the backbone to extract structural features, while the relative associations of geometry are underexplored, leading to non-optimal grasp prediction results. In this work, a parallelized graph-based pipeline is developed to solve the 7-DoF grasp pose generation problem with point

Automating fabric manipulation in garment manufacturing remains a challenging task due to the characteristics of limp sheet materials and the diversity of fabrics used. This paper introduces an adaptive and optimized robotic fabric handling system, designed to address these challenges. The system comprises an industrial robot, four needle grippers, and a novel adaptive gripper jig system capable of

Owing to the advantages of good flexibility and low cost, robots are gradually replacing manual labor as an effective carrier for the grinding and polishing of aeroengine blades. However, the geometric features of blades are complex and diverse, and the contour accuracy and surface quality requirements are high, making the robotic grinding and polishing of blades still a challenging task. For this

This article focuses on improving the compliance, efficiency, and robustness of batch precision assembly of small-scale pegs flexibly absorbed by a suction cup. The main contribution is that a force–vision fusion fuzzy control method (FVFFC) is proposed to achieve precision assembly with unknown clearance or interference fit. Both visual and force features are designed to describe the state of the

In recent years, with the deepening integration of digital twins (DT) and the Industrial Internet of Things (IIoT), solutions based on digital twins have been widely applied in IIoT scenarios. However, most existing solutions tend to overlook the latency issue during the interaction between mobile devices, such as industrial mobile robots (IMR), and their DTs while in motion. Excessive interaction

This study presents the Reconfigurable and Responsive Robot Manufacturing (R3M) architecture, a novel framework engineered to autonomously adapt to fluctuating product variants and demands within manufacturing environments. At the heart of R3M lies an integrated architecture that ensures a seamless data flow between critical modules, facilitated by an advanced communication platform. These modules

Point clouds are widely used to construct models of workpieces using 3D scanners, especially where high-quality robotic and automatic 3D scanning is required in industries and manufacturing. In recent years, Point Cloud Quality Assessment (PCQA) has garnered increasing attention as it provides quality scores for entire point clouds, addressing issues such as downsampling and compression distortions

Virtual Reality (VR) and Augmented Reality (AR) technologies have been separately applied to enhance a wide range of design and manufacturing operations across various industries. Most VR applications are primarily focused on product prototyping and personnel training, whereas AR is commonly used to facilitate manual operations in manufacturing such as assembly and maintenance tasks. This study proposes

In automated fiber placement (AFP), addressing the continuous motion planning challenge of redundant layup manipulators in complex environments, this paper proposes an offline redundancy optimization algorithm based on improved RRT* (Rapidly-exploring Random Trees). This algorithm maximizes the utilization of kinematic redundancy to derive smooth joint trajectories devoid of collisions and singularities

In emerging manufacturing facilities, robots must enhance their flexibility. They are expected to perform complex jobs, showing different behaviors on the need, all within unstructured environments, and without requiring reprogramming or setup adjustments. To address this challenge, we introduce the A3CQP, a non-strict hierarchical Quadratic Programming (QP) controller. It seamlessly combines both

Digital Twin (DT) technology, which integrates multi-source information, is extensively applied for comprehensive monitoring, predicting, and optimizing manufacturing processes. The core of this technology is the Digital Twin Virtual Model (DTVM), which acts as a virtual mirror reflecting the real-world physical processes within a digital environment. In processes like tube bending, constructing a

A robotic grinding system requires a force-controlled grinding module to provide a consistent surface roughness and a robot arm to position the grinding module to reach a wide range of surface area on a workpiece. Existing pneumatic grinding modules are heavy and bulky and cannot provide very accurate force control. Articulated 6-axis robot arms are often used for positioning the grinding module, but

Digital Twin (DT) is a promising technology that offers versatile services to enhance manufacturing intelligence. However, the agility, reliability and analysis capabilities of existing DT services are severely challenged when applied and deployed at large-scale production lines. To address the aforementioned issues, a microservice-based DT system with redundant architecture is proposed. First, a scalable

Freeform surface parts play a significant role in the aerospace industry, the mold- manufacturing industry and the automobile industry, and it is energy-saving, material-saving, time-saving and environmentally beneficial to remanufacture the damaged components to restore their functionality and performance. Due to the complex geometry of the freeform surface wear, the adaptive remanufacturing of freeform

Human-centric assembly is emerging as a promising paradigm for achieving mass personalization in the context of Industry 5.0, as it fully capitalizes on the advantages of human flexibility with robot assistance. However, in small-batch and highly customized assembly tasks, frequently changes in production procedures pose significant cognition challenges. To address this, leveraging computer vision

For dynamic collision-free trajectory planning in dual-robot and human collaborative tasks, this paper develops an online dual-robot Mutual Collision Avoidance (MCA) scheme based on convex optimization. A novel convex optimization formulation model, named Disciplined Convex programming by Shifting reference paths (DCS), is proposed for solving the single-robot trajectory optimization problem. Furthermore