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High precision assembly processes using industrial robots require the process parameters to be tuned to achieve desired performance such as cycle time and first time through rate. Some researchers proposed methods such as design-of-experiments (DOE) to obtain optimal parameters. However, these methods only discuss how to find the optimal parameters if the part and/or workpiece location errors are in a certain range. In real assembly processes, the part and/or workpiece location errors could be different from batch to batch. Therefore, the existing methods have some limitations. This paper aims to improve the process parameter optimization method for complex robotic assembly process.

In this paper, the parameter optimization process based on DOE with different part and/or workpiece location errors is investigated. An online parameter optimization method is also proposed.

Experimental results demonstrate that the optimal parameters for different initial conditions are different and larger initial part and/or workpiece location errors will cause longer cycle time. Therefore, to improve the assembly process performance, the initial part and/or workpiece location errors should be compensated first, and the optimal parameters in production should be changed once the initial tool position is compensated. Experimental results show that the proposed method is very promising in reducing the cycle time in assembly processes.

The proposed method is practical without any limitation.

The proposed technique is implemented and tested using a real industrial application, a valve body assembly process. Hence, the developed method can be directly implemented in production.

This paper provides a technique to improve the assembly efficiency by compensating the initial part location errors. An online parameter optimization method is also proposed to automatically perform the parameter optimization process without human intervention. Compared with the results using other methods, the proposed technology can greatly reduce the assembly cycle time.

This paper aims to develop a strategy for high‐precision assembly in a semi‐structured environment based on vision and force control.

The position and orientation of a part are identified using the vision system. The force/torque control algorithm is then applied to perform a tight‐tolerance assembly that is a high‐precision assembly.

The tight tolerance assembly in a semi‐structured environment is successfully implemented using vision guidance and force/torque‐control strategy.

The developed methodology can be applied to tight tolerance assembly, such as forward‐clutch assembly, torque‐converter assembly, etc.

An industrial assembly methodology has been developed and implemented for high‐precision assembly in a semi‐structured environment. This innovation has many potential applications in automotive manufacturing.

Paint path planning for industrial robots is critical for uniform paint distribution, process cycle time and material waste, etc. However, paint path planning is still a costly and time‐consuming process. Currently paint path planning has always caused a bottle‐neck for manufacturing automation because typical manual teaching methods are tedious, error‐prone and skill‐dependent. Hence, it is essential to develop automated tool path‐planning methods to replace manual paint path planning. The purpose of this paper is to review the existing automated tool path‐planning methods, and investigate their advantages and disadvantages.

The approach takes the form of a review of automated tool path‐planning methods, to investigate the advantages and disadvantages of the current technologies.

Paint path planning is a very complicated task considering complex parts, paint process requirements and complicated spraying tools. There are some research and development efforts in this area. Based on the review of the methods used for paint path planning and simulation, the paper concludes that: the tessellated CAD model formats have many advantages in paint path planning and paint deposition simulation. However, the tessellated CAD model formats lack edge and connection information. Hence, it may not be suitable for some applications requiring edge following, such as welding. For the spray gun model, more complicated models, such as 2D models, should be used for both path planning and paint distribution simulation. Paint path generation methods should be able to generate a paint path for complex automotive parts without assumptions, such as presupposing a part with a continuous surface.

The paper makes possible automated path generation for spray‐painting process using industrial robots such that the path‐planning time can be reduced, the product quality improved, etc.

The paper provides a useful review of current paint path‐planning methodologies based on the CAD models of parts.

Moving production lines are widely used in many manufacturing factories, such as automotive and general industries. However, industrial robots are hardly used to perform any tasks on the moving production lines. One of the main reasons is that it is difficult for conventional industrial robots to adjust to any sort of change. Therefore, the authors developed an industrial robotic system to track the random motion of the moving production lines while performing assembly processes. Before setting up a physical system to measure the system performance, it is desirable to develop a method to analyze the system performance. The purpose of this paper is to develop a performance analysis method for a robotic assembly system on a moving production line.

The developed system is based on the synergic combination of visual servoing and force control technology. Since it is difficult to model the system accurately, a second‐order system is used to approximate it. The system performance for force control and visual servoing is then analyzed. The tracking errors are calculated and compared with experimental results.

The developed method is evaluated using an experimental system and simulation. The simulation results are quite close to the experimental results. Hence, the developed method can be used to estimate the system performance.

Since only one system is set up to validate the developed method, more testing is needed to generalize it.

The developed technology is validated using the experimental results and the results are promising. Even though there is a limitation, the developed method can be used to estimate the system performance before setting up a physical system.

This paper provides a system performance analysis method for a robotic assembly on a moving production line. It is important to estimate the system performance before setting up a physical system because it will save a lot of time and resources in the manufacturing floor.

The purpose of this paper is to develop an intelligent robot assembly system for the moving production line. Moving production lines are widely used in many manufacturing factories, including automotive and general industries. Industrial robots are hardly used to perform any tasks on the moving production lines. One of the main reasons is that it is difficult for conventional industrial robots to adjust to any sort of change. Therefore, more intelligent industrial robotic systems have to be developed to adopt the random motion of the moving production lines. This paper presents an intelligent robotics system that performs an assembly process while the object is moving, using synergic combination of visual servoing and force control technology.

The developed intelligent robotic system includes some rules to ensure the success of the assembly processes. Also visual servoing and force control are used to deal with the random motion of the moving objects. Since the objects on the moving production lines are moving with random speed, visual servoing is adopted to tracking the motion of the moving object. Force control is also integrated to control the motion of the robot and keep the robotic system compliant with the moving objects to avoid the damage of the whole system.

The developed intelligent robotic technology has been successfully implemented. The wheel loading process is used as example.

Since the developed technology is based on the low‐level motion control, safety has to be considered. Currently, it is done by motion supervision.

The developed technology can be used to perform assemblies in the moving production lines. Since the developed platform is based on the synergic combination of visual servoing and force control technology, it can be used in other areas, such as seam tracking and seat loading, etc.

This paper provides a practical solution of performing assemblies on the moving production lines, which is not available on the current industrial robot market.

This paper seeks to establish parallel robots with strong performance characteristics in handling and assembly processes.

The presented work introduces concepts and solutions related to the improvement of parallel kinematic mechanisms. Structural design topics and modeling approaches are as well considered as control schemes and new machine components particularly designed for high‐dynamic parallel robots. The results have been achieved by a unique interdisciplinary research group linking knowledge from mechanical engineering, electrical engineering and computer science.

The paper found numerous individually applicable methods leading to an improved efficiency of parallel robots. Several of the developments have been already implemented and validated by various self‐built machine prototypes and a new control system.

Owing to higher stiffness, accuracy and improved dynamic behavior parallel robots proved to be an efficient and suitable supplement to serial robots. By means of the various developments contributed in this paper, the promising potential of this class of robots is once more emphasized and further strengthened.

The purpose of this paper is to systematically review the published slicing methods for additive manufacturing (AM), especially the multi-direction and non-layerwise slicing methods, which are particularly suitable for the directed energy deposition (DED) process to improve the surface quality and eliminate the usage of support structures.

In this paper, the published slicing methods are clarified into three categories: the traditional slicing methods (e.g. the basic and adaptive slicing methods) performed in the powder bed fusion (PBF) system, the multi-direction slicing methods and non-layerwise slicing methods used in DED systems. The traditional slicing methods are reviewed only briefly because a review article already exists for them, and the latter two slicing methods are reviewed comprehensively with further discussion and outlook.

A few traditional slicing approaches were developed in the literature, including basic and adaptive slicing methods. These methods are efficient and robust when they are performed in the PBF system. However, they are retarded in the DED process because costly support structures are required to sustain overhanging parts and their surface quality and contour accuracy are not satisfactory. This limitation has led to the development of various multi-direction and non-layerwise slicing methods to improve the surface quality and enable the production of overhangs with minimum supports.

An original review of the AM slicing methods is provided in this paper. For the traditional slicing methods and the multi-direction and non-layerwise slicing method, the published slicing strategies are discussed and compared. Recommendations for future slicing work are also provided.