Roller hemming is a relatively new process used to achieve high-precision assembly of auto-body enclosure panels. During the process of roller hemming, accuracy of the roller pose and trajectory affects the hemming quality of the product. The traditional passive method based on robot teaching to determine the pose of the roller is inefficient and time-consuming. In these studies, we proposed an active

Automatic robotic grinding and polishing systems have become a developing trend in aerospace parts manufacturing. In a robotic blade grinding and polishing system (RBGPS), the automatic and precise calibration of the dynamic workpiece coordinate frame is the most important process. In this research, a new method that introduces the concept of six-point positioning into the dynamic workpiece coordinate

Abstract not available

Position error is a significant limitation for industrial robots in high-precision machining and manufacturing. Efficient error measurement and compensation for robots equipped with end-effectors are difficult in industrial environments. This paper proposes a robot calibration method based on an elasto–geometrical error and gravity model. Firstly, a geometric error model was established based on the

The features of collaborative robots (cobots), like lightweight, easy programming, and flexibility, meet the production automation requirements in SMEs. However, SME productions are usually in semi-structured or cluttered environments, which raises major challenges in implementing cobot systems in SME production, for instance, increasing the visual perception of cobots, handling diverse tasks, and

MoveIt is the primary software library for motion planning and mobile manipulation in ROS, and it incorporates the latest advances in motion planning, control and perception. However, it is still quite recent, and some important functions to build more advanced manipulation applications, required to robotize many manufacturing processes, have not been developed yet. MoveIt is an open source software

Multi-camera vision is widely used for guiding the machining robot to remove flash and burrs on complex automotive castings and forgings with arbitrary initial posture. Aiming at the problems of insufficient field of vision and regional occlusion in actual machining, a gradient-weighted multi-view calibration method (GWM-View) is proposed for the machining robot positioning based on the convergent

Currently, expectations of shorter time-to-market and improved product performance are placing greater demands on manufacturing companies. However, the optimization and redesign work between the design stage and the prototype design and manufacturing stage in the traditional product development process lengthens the required product development cycle time (which lasts up to several years in extreme

The multi-pipe intersection structure in form of co-main pipe is widely used in various industries. To improve its welding quality and efficiency, this paper is devoted to proposing an offline programming approach to the robot trajectory based on NSGA-Ⅱ and measured 3D point-clouds. First, considering the existence of deviation between the actual workpiece and its ideal model, this paper selects the

The poor pose accuracy of industrial robots restricts their further application in aviation manufacturing. Kinematic calibration based on position errors is a traditional method to improve robot accuracy. However, due to the difference between length errors and angle errors in the order of magnitude, it is difficult to accurately calibrate these geometric parameters together. In this paper, a two-step

Industrial composite fiber has been widely used in the high-end manufacturing because of its superior stiffness and strength. To ensure the quality of composite fiber placement in making high-end and lightweight aerospace products, it needs reliable composite fiber layup in-situ inspection. An accurate seam width measurement is an indispensable procedure during the layup inspection. However, the traditional

Chatter occurs easily during robotic milling owing to the low structural stiffness of industrial robots and can degrade the machining quality or even cause robot failure. The accurate frequency response function (FRF) of the robot is essential for predicting chatter stability and selecting the appropriate process parameters. However, the FRF of a robot is affected by multiple factors, such as pose

A new lockable spherical joint is proposed in this paper, and it can be used as a revolute joint, a universal joint or a spherical joint. Three locking methods are introduced to construct the lockable spherical joint. Based on the proposed lockable spherical joint, a new reconfigurable parallel mechanism (RPM) with large positioning workspace is presented. The RPM has a tripod architecture with a lockable

The demands for mass individualization and networked collaborative manufacturing are increasing, bringing significant challenges to effectively organizing idle distributed manufacturing resources. To improve production efficiency and applicability in the distributed manufacturing environment, this paper proposes a multi-agent and cloud-edge orchestration framework for production control. A multi-agent

3D object pose estimation for robotic grasping and manipulation is a crucial task in the manufacturing industry. In cluttered and occluded scenes, the 6D pose estimation of the low-textured or textureless industrial object is a challenging problem due to the lack of color information. Thus, point cloud that is hardly affected by the lighting conditions is gaining popularity as an alternative solution

Skill learning in robot polishing is gaining attention and becoming a hot issue. Current studies on skill learning in robot polishing are mainly about trajectory skills, and force-relevant skills learning models are less studied. A skill learning method with good generalization and robustness is one of the elements worth investigating. In this study, a force-relevant skills learning method called arc-length

Current advances in Task and Motion Planning (TAMP) framework often rely on a specific and static task structure. A task structure is a sequence of how work pieces should be manipulated towards achieving a goal. Such systems can be problematic when task structures change as a result of human performance during human-robot collaboration scenarios in manufacturing or when redundant objects are present

In teleoperation, a force feedback device is a medium to build a transparent interaction environment between a human and a remote robotic arm. Using force feedback devices, the users can operate the remote robotic arm intuitively and perceive remote interaction through the force channel, just as if they are in the remote environment. Compared with impedance devices, admittance devices have the advantages

With the progressive digitalization in industrial manufacturing, the usage of complex robotic systems in both intralogistics and production is expected to increase. This proposes a challenge for planners and shop floor workers, as programming and interacting with these various systems leads to a high cognitive load. Especially the broad range of different manufacturer specific software leads to a number

The previous studies on the flexible job shop scheduling problems (FJSP) with machine flexibility and worker flexibility normally assume that each machine is operated by one worker at any time. However, it is not accurate in many cases because many workers may be required for machines in processing complex operations. Hence, this paper studies a universal version, i.e., FJSP with worker cooperation

Automatic robot grinding technology has been widely applied in the modern manufacturing industry. A flexible abrasive belt wheel used to grind the weld can avoid burns on the base material and improve the processing efficiency. However, when the robot grinds a weld seam, the material removal depth does not coincide with the feed depth because of the soft contact and uneven weld height, affecting the

Abstract not available

Digital twins and artificial intelligence have shown promise for improving the robustness, responsiveness, and productivity of industrial systems. However, traditional digital twin approaches are often only employed to augment single, static systems to optimise a particular process. This article presents a paradigm for combining digital twins and modular artificial intelligence algorithms to dynamically

Learning a stable dynamic system (DS) encoding human motion rules has been shown as an efficient approach for transferring motion skills. However, contradictions always exist between the stability, accuracy and generalization of the learned DS. This paper presents an approach to enhance the accuracy and generalization by learning a neural-shaped quadratic Lyapunov function (NS-QLF). For the stability

Safe and efficient robot manipulation in uncertain clustered environments has been recognized to be a key element of future intelligent industrial robots. Unlike traditional robots that work in structured and deterministic environments, intelligent industrial robots need to operate in dynamically changing and stochastic environments with limited computation resources. This paper proposed a hierarchical

The machine tool industry plays a major role in the execution of high-quality and efficient complex manufacturing processes. The adoption of digital technologies can transform production systems into more connected, adaptive, efficient, and potentially sustainable systems. A key enabler of this transformation is servitization, a business model that builds on digitalization and data capture to deliver

Recent development in the Wire arc additive manufacturing (WAAM) provides a promising alternative for fabricating high value-added medium to large metal components for many industries such as aerospace and maritime industry. However, challenges stemming from the demand for increasingly complex and high-quality products, hinder the widespread adoption of the conventional WAAM method for manufacturing

The increased levels of complexity in manufacturing lead to increased potential occupational health and safety (OHS) and operational risks. Dealing with this requires new approaches that are able to not only analyze complex systems in detail but also provide analysts an overall understanding of the studied system. This study aims to introduce a novel approach integrating Functional Resonance Analysis

This paper is focused on assembly tasks executed by an industrial robotic manipulator in the presence of uncertainties. The goal is to achieve higher levels of autonomy and flexibility of robotic systems in the execution of such tasks. In particular, as a well-established paradigm of assembly tasks, a Peg-in-Hole task has been considered, where the pose of the target object with respect to the robot

Lower path accuracy is an obstacle to the application of industrial robots in intelligent and precision grinding complex surfaces. This paper proposes a novel path accuracy enhancement strategy and different evaluation methods for a six-degree-of-freedom industrial robot FANUC M710ic/50 used for grinding an aero-engine blade. Six groups of theoretical tool paths individually planned on this complex

Defect detection is a critical measurement process for intelligent manufacturing systems to provide insights for product quality improvement. For complex products such as integrated circuit wafers, several types of defects are usually coupled in a piece of wafer to form a mixed-type defect, which poses a challenge to current defect detection methods. This paper proposed a knowledge augmented broad

The combination of Augmented Reality (AR) and Digital Twin (DT) has begun to show its potential nowadays, leading to a growing research interest in both academia and industry. Especially under the current human-centric trend, AR embraces the potential to integrate operators into the new generation of Human Cyber–Physical System (HCPS), in which DT is a pillar component. Some review articles have focused

Research and application of reinforcement learning in robotics for contact-rich manipulation tasks have exploded in recent years. Its ability to cope with unstructured environments and accomplish hard-to-engineer behaviors has led reinforcement learning agents to be increasingly applied in real-life scenarios. However, there is still a long way ahead for reinforcement learning to become a core element

Due to its excellent chemical and mechanical properties, silicone sealing has been widely used in many industries. Currently, the majority of these sealing tasks are performed by human workers. Hence, they are susceptible to labor shortage problems. The use of vision-guided robotic systems is a feasible alternative to automate these types of repetitive and tedious manipulation tasks. In this paper

This paper looks at the problem of reducing the energy use of robot movements in a robot station with stochastic execution times, while keeping the productivity of the station. The problem is formulated as a stochastic optimization problem, that constrains the makespan of the station to meet a deadline with a high probability. The energy use of the station is a function of the execution times of the

The laser tracker has been used as the mainstream instrument for the position accuracy calibration of industrial robots for quite a long time. However, due to the complexity of the built-in dual-axis active servo tracking system, its cost is high and the target reflector has to adjust its pose frequently, so it cannot be popularized in the production and application sites of industrial robots. Based

Automated guided vehicles (AGVs) are a key technology to facilitate flexible production systems in the context of Industry 4.0. This paper investigates an optimization model and a solution using a decentralized multi-agent approach for a new capacitated multi-AGV scheduling problem with conflicting products (CMASPCP) to take full advantage of AGVs. The novelty of the problem and our model lies in the

Human–Robot Collaboration (HRC) has a pivotal role in smart manufacturing for strict requirements of human-centricity, sustainability, and resilience. However, existing HRC development mainly undertakes either a human-dominant or robot-dominant manner, where human and robotic agents reactively perform operations by following pre-defined instructions, thus far from an efficient integration of robotic

Remanufacturing is an emerging eco-friendly industry because it consumes less energy, cost, and material to manufacture like-new parts with a warranty to match. However, restoration processes are ad-hoc and complex because the "raw" materials for remanufacturing are returned used parts, which exhibit significant uncertainties in failure features involving failure location, failure mode, failure volume

This paper presents a robot teaching system based on hand-robot contact state detection and human motion intent recognition. The system can detect the contact state of the hand-robot joint and extracts motion intention information from the human surface electromyography (sEMG) signals to control the robot's motion. First, a hand-robot contact state detection method is proposed based on the fusion of

Traditionally, industrial robots are programmed by highly specialized workers that either directly write code in platform-specific languages, or use dedicated hardware (teach-pendant) to move the robot through the desired via-points. Unsurprisingly, the inherently complex and time-consuming nature of this task is one of the factors that are still preventing industrial manipulators from being massively

Tool wear prediction is of significance to reduce energy consumption through cutting parameter optimization. However, the current studies ignore the effect of machine aging on the tool wear prediction model, and their cutting parameter optimization methods cannot cope with the dynamic change of tool wear in the machining process. Thus, a reinforcement learning-enabled integrated method of tool wear

Remanufacturing system scheduling is an essential and effective approach to realize the digitization and greening of the remanufacturing industry. However, previous researches on the remanufacturing system scheduling problem mainly consider a single or two production stages and economic objectives. In this paper, by integrating the three core production stages, i.e., disassembly, reprocessing and reassembly

Chatter vibration is one of the main factors that limit the productivity and quality of the robotic milling process. To predict the robotic milling stability, it is essential to obtain the tool tip frequency response function (FRF). The tool tip dynamics of a robot heavily depend on its postures and used tools. A state-of-art methodology of combining the regression model with the Receptance Coupling

This paper presents an open-architecture of CNC system and mirror milling technology for a new-type 5-axis hybrid robot named TriMule. The CNC system with dual CPUs is developed first to achieve human-computer interaction and motion control. Then, three key technologies are integrated in the system for improving the control quality, including singularity avoidance, feedforward control considering joint

In an Industry 4.0 Factory, physical entities such as humans, machines and materials are digitized into digital twins (DT) with smart IoT (Internet of Things) devices resulting in Cyber-Physical Production Systems (CPPS). Real-time data analytics builds up traceability and visibility, not only in the physical domain but also cyber space. This paper adds a new concept of cyber-physical inventory or

Steel is a basic material, and vision-based defect recognition is important for quality. Recently, deep learning, especially convolutional neural network (CNN), has become a research hotspot. However, steel defects have poor class separation, which is similar to the background, and different defects show similar textures. This causes some defects unrecognizable and influences production greatly. Thus

The mobile robot is the essential equipment for automated logistics in the intelligent workshop, but the literature on shop scheduling rarely considers transport resources. This paper studies the integrated scheduling of machines and mobile robots, which can facilitate the efficiency of production systems. For the job shop scheduling problem with mobile robots (JSPMR), the existing mathematical models

Tool breakage occurs randomly during machining operations, which induces more severe impacts on the quality of components compared to progressive tool wear. It is widely acknowledged that the unpredictable changes in cutting conditions will cause fluctuations in the signal amplitude and thus generate false alarms. This study introduced a novel method for tool breakage monitoring based on dimensionless

Establishing accurate dynamic models in a form that is suitable for integration with model-based control methods, is of great significance for further improving the dynamic motion control precision of ball-screw drives. However, due to the nonlinear time-varying factors such as position-dependent dynamics and nonlinear friction disturbance, it is difficult to model the dynamic characteristics of ball-screw

Automatic joint motion planning is very important in robotic wheel hub polishing systems. Higher flexibility is achieved based on the joint configuration with multiple solutions, which means that the robot has kinematic redundancy for machining tasks. Redundant joints can be used to optimize the motion of the robot, but less research has been done on multi-dimensional redundant optimization. In this

Automatic and fast weld type classification, tacked spot recognition and weld ROI (region of interest) determination are key links for intelligent welding robot, because they directly affect the seam tracking and welding parameters such as current, voltage and torch inclination. Nevertheless, there are few studies on weld type classification, tacked spot recognition, and weld ROI determination. Considering

The commissioning of Computerized Numerical Control Machine Tools (CNCMTs) is particularly important and the commissioning quality directly affects its product processing. However, traditional commissioning methods are not suitable for complex and changeable machining conditions during operation, and the derived commissioning results have limited effectiveness. Therefore, this paper proposes a digital

Cutting parameters play a major role in improving the energy efficiency of the manufacturing industry. As the main processing method for aviation parts, flank milling usually adopts multi-pass constant and conservative cutting parameters to prevent workpiece deformation but degrades energy efficiency. To address the issue, this paper proposes a novel multi-pass parametric optimisation based on deep

Industrial robots form an integral part of today's manufacturing industry, due to their high versatility, precision, and fatigue proof nature. Yet, many small and medium sized enterprises (SMEs) still predominantly rely on manual labor. The main barriers that prevent SMEs from utilizing robots to a larger degree are described to be the large initial investment, uncertainty about costs (total cost of

Based on the holistic data of product-service system (PSS) delivery processes, equipment portrait can be used to describe personalised user requirements and conduct targeted analysis on the performance of complex products. Therefore, a promising application combining PSS and equipment portrait is to establish a more refined portrait model to improve the accuracy and applicability of operation and maintenance