The complicated task allocation, scheduling and planning problem with multiple stations and multiple robots commonly seen in spot welding production line design is studied in this paper. To deal with the highly coupled model combined with several task planning sub-problems, including robot cells design, robots allocation among cells, welding allocation among cells and robots, and welding scheduling

Contact force and torque sensing approaches enable manipulators to cooperate with humans and to interact appropriately with unexpected collisions. In this paper, a mode-switching moving average with variable time period is proposed to reduce the effects of measured motor current noise and thus provide improved confidence in joint output torque estimation. The time period of the filter adapts continuously

Cloud Manufacturing (CMfg), a new manufacturing paradigm, enables an opportunity for manufacturing enterprises to respond to a wide variety of demands. The CMfg concept integrates the distributed resources and capacities in a shared economy, transfers them to the virtual manufacturing services with various quality of service (QoS) properties. These services are invoked to collaborate in producing customized

The presence of cooperation between robots and machines in the industrial environment improved the solution for several manufacturing problems. With cooperation, new challenges emerged, and among these stands out the collision avoidance between such robots and machines. Collision avoidance can be dealt with in several ways, taking into account the computational effort to make a decision and the quality

This study considers a flowshop type production system consisting of m machines. A material handling robot transports the parts between the machines and loads and unloads the machines. We consider the sequencing of the robot moves and determining the speeds of these moves simultaneously. These decisions affect both the robot’s energy consumption and the production speed of the system. In this study

Part integration is to integrate parts to be a fabrication and assembly unit. It can effectively reduce the fabrication and assembly unit quantity of a product and has been deemed as an effective way to promote the productivity of manufacturing. Although additive manufacturing (AM) has great potential to further promote the part integration for any product (assembly) model, part integration works using

Installation or even just modification of robot-supported production and quality inspection is a tedious process that usually requires full-time human expert engagement. The resulting parameters, e.g. robot velocities specified by an expert, are often subjective and produce suboptimal results. In this paper, we propose a new approach for specifying visual inspection trajectories based on CAD models

Surface finishing, as the final stage in the manufacturing pipeline, is a key process in determining the quality and life span of a product. Such a task is characterized by low contact forces and minimal material removal from the object surface. Despite the advancements in machine learning and artificial intelligence, human workforce is still irreplaceable in performing such tasks due to superior dexterity

Rapid advances in sensing and communication technologies connect isolated manufacturing units, which generates large amounts of data. The new trend of mass customization brings a higher level of disturbances and uncertainties to production planning. Traditional manufacturing systems analyze data and schedule orders in a centralized architecture, which is inefficient and unreliable for the overdependence

The ever increasingly stringent performance requirements of industrial robotic applications highlight significant importance of advanced robust control designs for serial robots that are generally subject to various uncertainties and external disturbances. Therefore, this paper proposes and investigates the design and implementation of a robust adaptive fuzzy sliding mode controller in the task space

The linear-format path is widely adopted to approximate the continuous contour in robot controllers. The tangential discontinuity of the linear paths usually causes the discontinuity of the joint velocity. To comply with the joint kinematics limits, the robots have to stop at each corner point, resulting in a great loss of efficiency. To achieve a smooth motion, this paper presents an analytical decoupled

Flexible job shop scheduling is one of the most effective methods for solving multiple varieties and small batch production problems in discrete manufacturing enterprises. However, limitations of actual transportation conditions in the flexible job shop scheduling problem (FJSP) are neglected, which limits its application in actual production. In this paper, the constraint influence imposed by finite

In an assembly task, stage identification determines the subsequent parts to be assembled and therefore, it affects the quality and efficiency of the entire assembly operation in computer-aided manufacturing. However, due to the similarity between the assemblies in two adjacent stages, it is difficult to distinguish the assembly accurately based on the current visual recognition method. Considering

As one of the critical elements for smart manufacturing, human-robot collaboration (HRC), which refers to goal-oriented joint activities of humans and collaborative robots in a shared workspace, has gained increasing attention in recent years. HRC is envisioned to break the traditional barrier that separates human workers from robots and greatly improve operational flexibility and productivity. To

This study proposes a 3-phase solution approach for a multi-product parallel multi-stage cellular manufacturing company. The study focuses on a case study involving a shoe manufacturing plant in which products are produced according to their due dates. The investigated manufacturing process has three stages, namely lasting cells, rotary injection molding cells, finishing-packaging cells. System performance

The application of non-destructive evaluation approaches has attracted strong interests in modern automotive industries. This study presents an autonomous deep-computing framework to analyze raw videos from infrared systems and to predict weld nugget shape and size with unprecedented accuracy and speed. In a comprehensive training and testing experiment with 90 videos (seven sets of welding material

The Digital Twin concept, as the cutting edge of digital manufacturing solution for modern industries, plays a significant role in the Industry 4.0 era. One key enabling technology for developing a DT is the information modeling of physical products, so as to combine the physical world with the cyberspace more extensively and closely. Therefore, the modeling approach to managing as-fabricated data

Manufacturing challenges are driving the move from separated workspaces of either humans or robots towards a close, symbiotic collaboration. Symbiotic Human-Robot Collaboration requires both parties to not only share the same workspace, but to also perform tasks simultaneously. This raises questions of mutual awareness, for which safety is a critical factor. Despite advances regarding safety systems

This paper provides a review of research into using Augmented Reality (AR) and Mixed Reality(MR) for remote collaboration on physical tasks. AR/MR-based remote collaboration on physical tasks has recently become more prominent in academic research and engineering applications. It has great potential in many fields, such as real-time remote medical consultation, education, training, maintenance, remote

To fully disclose potential configurations of parallel mechanisms (PMs) that are performance-comparable to the commercially successful Exechon, a family of one translational two rotational (1T2R) over-constrained Exechon inspired PMs is synthesized through the screw theory. The synthesized PMs are further comparatively analyzed in terms of inverse kinematics, singularity occurrence and reachable workspace

This paper proposes a new calibration method for joint-dependent geometric errors of six-DoF industrial robots. Chebyshev polynomials are adopted to characterize the high-order joint-dependent geometric error model, revealing the impact of strain wave gearing errors and other sources more accurately. This effort also brings higher observability index on condition of an appropriate order. Furthermore

Augmented Reality (AR) has the potential for facilitating the interaction with robots by enhancing the operator’s spatial understanding as well as providing further cognitive support, e.g. in order to make manual programming processes more efficient and provide on-site simulation. However, we consider major issues that prevent a widespread use of AR towards robotics in industries. Initially, the commissioning

Predictive maintenance has been proposed to maximize the overall plant availability of modern manufacturing systems. To this end, research has been conducted mainly on data-driven prognostic techniques for machinery equipment individual components. However, the lack of historical data together with the intricate design of industrial machines, e.g. robots, stimulate the use of advanced methods exploiting

The robotic grasping task persists as a modern industry problem that seeks autonomous, fast implementation, and efficient techniques. Domestic robots are also a reality demanding a delicate and accurate human–machine interaction, with precise robotic grasping and handling. From decades ago, with analytical heuristics, to recent days, with the new deep learning policies, grasping in complex scenarios

Simulation is capable to cope with the uncertain and dynamic nature of industrial value chains. However, in-depth system expertise is inevitable for mapping objects and constraints from the real world to a virtual model. This knowledge-intensity leads to long development times of respective projects, which contradicts the need for timely decision support. Since more and more companies use industrial

Contact force estimation enables robots to physically interact with unknown environments and to work with human operators in a shared workspace. Most heavy-duty industrial robots without built-in force/torque sensors rely on the inverse dynamics for the sensorless force estimation. However, this scheme suffers from the serious model uncertainty induced by the nonnegligible noise in the estimation process

The disassembly process is the main step of dealing with End-Of-Life (EOL) products. This process is carried out mostly manually so far. Manual disassembly is not efficient economically and the robotic systems are not reliable in dealing with complex disassembly operations as they have high-level uncertainty. In this research, a disassembly planning method based on human-robot collaboration is proposed

In this paper we discuss our evolved understanding on the meaning of agile robotics. The lessons learned are concluded from the four years of our participation in ARIAC, the Agile Robotics for Industrial Automation Competition, that we managed to win in 2020. After elaborating on ARIAC tasks, challenges and scoring and their consequences on algorithm design, error handling and software development

The rapid development of information and communication technologies has triggered the proposition and implementation of smart manufacturing paradigms. In this regard, efficient allocation of smart manufacturing services (SMSs) can provide a sustainable manner for promoting cleaner production. Currently, centralized optimization methods have been widely used to complete the optimal allocation of SMSs

Augmented reality (AR)-based programming using the demonstration method has been widely studied. However, studies on AR-based programming for remote robots are lacking because of the limitation of human–computer interaction. This paper proposes an AR-based robot teleoperation system and method using RGB-D imaging and an attitude teaching device. By sending the color and depth images of the remote robot

The approach of Learning from Demonstrations (LfD) can support human operators especially those without much programming experience to control a collaborative robot (cobot) in an intuitive and convenient means. Gaussian Mixture Model and Gaussian Mixture Regression (GMM and GMR) are useful tools for implementing such a LfD approach. However, well-performed GMM/GMR require a series of demonstrations

Five-axis continuous scanning inspection is an emerging technology in measuring free-form surfaces. Compared to the traditional three-axis scanning inspection, the five-axis continuous surface scanning tremendously boosts the inspection efficiency and suffers from less dynamic error due to adopting a special sweep scanning working mode, which lets the super-light and high-speed rotary two-axis probe

A typical manufacturing process consists of a machining (material removal) process followed by an inspection system for the quality checks. Usually these checks are performed at the end of the process and they may also involve removing the part to a dedicated inspection area. This paper presents an innovative perturbation signal based data generation and machine learning approach to build a robust

Production scheduling plays an important role in the intelligent decision support system and intelligent optimization decision technology. In the context of the globalization trend, the current production and management may extend from a single factory to a distributed production network. In this paper, we study the distributed blocking flowshop scheduling problem (DBFSP) that is an important generalization

Dynamic personalized orders demand and uncertain manufacturing resource availability have become the research hotspots of intelligent resource optimization allocation. Currently, the data generated from the manufacturing industry are rapidly expanding. Such data are multi-source, heterogeneous and multi-scale. Transforming the data into knowledge to optimize the allocation between personalized orders

The poor absolute positioning accuracy of industrial robots is the main obstacle for its further application in precision grinding of complex surfaces, such as blisk, blade, etc. Based on the established kinematic error model of a typical industrial robot FANUC M710ic/50, a novel kinematic parameters calibration method is proposed in this paper to improve the absolute positioning accuracy of robot

Obstacle avoidance is a significant skill not only for mobile robots but also for robot manipulators working in unstructured environments. Various algorithms have been proposed to solve off-line planning and on-line adaption problems. However, it is still not able to ensure safety and flexibility in complex scenarios. In this paper, a novel obstacle avoidance algorithm is proposed to improve the robustness

Kinematic error model plays an important role in the kinematic calibration of robot manipulators. In order to guarantee the best calibration result, the error model should meet the requirements of completeness, minimality and continuity. For the conventional serial robots, these issues have been intensively studied and a consensus has been reached during the past decades. However, for parallel manipulators

Together with the trends of mass personalization, flexible robotic applications become more and more popular. Although conventional robotic automation of workpiece manipulation seems to be solved, advanced tasks still need great amount of effort to be reached. In most cases, on-site robot programming methods, which are intuitive and easy to use, are not applicable in flexible scenarios. On the other

To meet the increasingly complex needs of customers, scheduling faces challenges of the high uncertainty of product arrival in customized manufacturing (CM). This paper proposes a semantic-level component-based scheduling method to solve the uncertainty via the integration of the information model and the computation model. In our proposal, we first construct a component-based framework to illustrate

The use of multiple cooperating robotic manipulators to assemble large aircraft structures entails the scheduling of many discrete tasks such as drilling holes and installing fasteners. Since the tasks have different tool requirements, it is desirable to minimize tool changes that incur significant time costs. We approach this problem as a multi-robot task allocation problem with precedence constraints

Mobile robot machining provides more flexible machining mode compared to the robot machining with a fixed base. However, its machining accuracy is frequently questioned. This paper focuses on the accuracy analysis in mobile robot machining. To evaluate the machining error qualitatively, the tool center point (TCP) error index is defined as the distance between the TCP and the designed machining point

In the robotic eye-in-hand measurement system, a hand-eye calibration method is essential. From the perspective of 3D reconstruction, this paper first analyzes the influence of the line laser sensor hand-eye calibration error on the 3D reconstructed point clouds error. Based on this, considering the influence of line laser sensor measurement errors and the need for high efficiency and convenience in

Combination of geometric and parametric approaches of kinematic identification is proposed in this article. The experimental strategy is similar to that used in geometric approach wherein each axis of the robot is actuated one after the other. This adds clarity to experimental strategy, which becomes ambiguous while solely using a conventional parametric approach. Therefore it is easier to conduct

The solder paste printing (SPP) is a critical procedure in a surface mount technology (SMT) based assembly line, which is one of the major attributes to the defect of the printed circuit boards (PCBs). The quality of SPP is influenced by multiple factors, such as the squeegee speed, pressure, the stencil separation speed, cleaning frequency, and cleaning profile. During printing, the printer environment

The stencil printing process (SPP) is a critical operation in surface mount technology (SMT) because it contributes to 60% of soldering defects. The complex relationships between solder paste volume transfer efficiency (TE) and the SPP variables make the control of the solder paste volume TE during production a challenging problem. This research aims to optimize the stencil printing parameters in real

While multi-robot cells are being used more often in industry, the problem of work-piece position optimization is still solved using heuristics and the human experience and, in most industrial cases, even a feasible solution takes a considerable amount of trials to be found. Indeed, the optimization of a generic performance index along a path is complex, due to the dimension of the feasible-configuration

Effective Prognostics and Health Management (PHM) for cutting tools during Computerized Numerical Control (CNC) processes can significantly reduce downtime and decrease losses throughout manufacturing processes. In recent years, deep learning algorithms have demonstrated great potentials for PHM. However, the algorithms are still hindered by the challenge of the limited amount data available in practical

Shared Manufacturing is a new mode of social manufacturing based on the principles of a sharing economy. This paper presents a scalable framework for blockchain-based Shared Manufacturing that preserves the transparency and immutability characteristics of transaction records, which is critical to building trust between entities in blockchain-based systems. We define a blockchain-based protocol for

With the intensification of globalization, the competition among various manufacturing enterprises has become increasingly fierce, enterprises are developing in the direction of the product diversification, zero inventory or low inventory, and scheduling in production management has become more complicated. In this paper, machine and workpiece were as objects to study the problem of workshop scheduling

Metal products are susceptible to factors such as cutting force, clamping force and heat in the machining process, resulting in product quality problems, such as geometric deformation and surface defects. The real-time observation and control of product quality are integral to optimizing machining process. Digital twin technologies can be used to monitor and control the quality of products via multi-scale

Cloud Manufacturing Service Composition (CMSC), as one of the key issues of Cloud Manufacturing (CMfg), has already attracted much attention. Existing researches on CMSC mainly focus on the optimization efficiency in ideal conditions, while scarcely focus on how to efficiently reconfigure CMSC when service exceptions occur. Uncertain service exceptions often occur during CMSC's execution in real-life