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This paper aims to solve the problem that the changing of groove size and assembly gap would affect the precision of the multi-pass path planning and the welding quality and realize the automatic welding of a thick plate.

First, a double-sided double arc welding (DSAW) system with a self-designed passive vision sensor was established, then the image of the groove was captured and the characteristic parameters of groove were extracted by image processing. According to the welding parameters and the extracted geometry size, multi-pass path planning was executed by the DSAW system.

A DSAW system with a self-designed passive vision sensor was established which can realize the welding thick plate by double-sided double arc by two robots. The clear welding image of the groove was acquired, and an available image processing algorithm was proposed to accurately extract the characteristic parameters of the groove. According to the welding parameters and the extracted geometry size, multi-pass path planning can be executed by the DSAW system automatically.

Gas metal arc welding is used for root welding and filler passes in DSAW. Multi-pass path planning for thick plate by Double-sided Double Arc Welding (DSAW) based on vision sensor was proposed.

This paper aims to propose a diverless weld bead maintenance welding technology to prevent the leakage of subsea oil and gas pipeline and solve the key problems in the maintenance of subsea pipeline.

Based on the analysis of the cross-section of the fillet weld, the multi-layer and multi-pass welding path planning of the submarine pipeline sleeve fillet weld is studied, and thus a multi-layer and multi-pass welding path planning strategy is proposed. A welding seam filling method is designed, and the end position of the welding gun is planned, which provides a theoretical basis for the motion control of the maintenance system.

The trajectory planning and adjustment of multi-layer and multi-pass fillet welding and the motion stability control of the rotating mechanism are realized.

It provides the basis for the prototype design of the submarine pipeline maintenance and welding robot system, and also lays the foundation for the in-depth research on the intelligent maintenance system of submarine pipeline.

The maintenance of diverless subsea pipeline is a new type of maintenance method, which can solve the problem of large amount of subsea maintenance work with high efficiency.

In any real time control system, its scheduling and control policy should be reassessed every time the state of the system changes. In large and complex systems, this could be a self‐defeating goal. Implementing real time control in such systems would require an enormous amount of computation time. Determination of discrete time interval (simulation window length) is the main objective of this study. To implement and demonstrate this methodology, we selected a Flexible Manufacturing System (FMS) which approximates a dynamic job shop. The Expert Control System (ECS) developed in this study integrated programmes for different functions and employed multi‐pass simulation to determine the best scheduling strategy in the system. The simulation output is then subjected to Analysis of Variance (ANOVA) and Newman‐Keuls′ range tests to obtain a “good” simulation window length for different performance criteria of optimisation.

Recently several authors have concentrated their efforts in developing models to determine the economic lot size for multi‐stage systems. This is due to the fact that an increasing number of organisations are implementing material requirements planning systems. Numerous models have been developed and tested on problems with finite and rolling horizons and with deterministic time varying demand patterns.

This paper aims to develop a feasible visual weld detection method to solve the problems in multi-layer welding detection (e.g. cover pass welding detection) for seam tracking and non-destructive testing. It seeks for an adaptive and accurate way to determine the edge between the seam and the base metal in the grayscale image of weld automatically. This paper tries to contribute to next-generation real-time robotic welding systems for multi-layer welding.

This paper opted for invariant moments to characterize the seam and the base metal for classification purposes. The properties of invariant moments, such as high degree of self-similarity and separation, affine invariance and repetition invariance, were discussed to verify the adaptability of the invariant moment in weld detection. Then, a weld detection method based on invariant moments was proposed to extract the edge between the seam and the base metal, including image division, invariant moment features extraction, K-Means adaptive thresholding, maximum connected domain detection and edge position extraction.

This paper highlights the significance of high degree of self-similarity and separation, affine invariance and repetition invariance of the invariant moment for weld detection. An adaptive, effective and accurate method is proposed to detect the edge between the seam and the base metal based on invariant moments.

It is necessary to verify the applicability of the proposed method in variable welding conditions further. Further works will focus on the establishment of a real-time seam tracking system during the whole multi-layer/multi-pass welding process based on such adaptive visual features.

This paper includes the implications for development of an adaptive and real-time weld detection method, which is expected to be applied to online seam tracking in multi-layer welding.

This paper presents an accurate weld detection method in multi-layer welding, overcoming difficulties in effectiveness, adaptability and efficiency of existing weld detection methods.

This paper aims to investigate a stereo vision-based hybrid (additive and subtractive) manufacturing process using direct laser metal deposition, computer numerical control (CNC) machining and in-process scanning to repair metallic components automatically. The focus of this work was to realize automated alignment and adaptive tool path generation that can repair metallic components after a single setup.

Stereo vision was used to detect the defect area for automated alignment. After the defect is located, a laser displacement sensor is used to scan the defect area before and after laser metal deposition. The scan is then processed by an adaptive algorithm to generate a tool path for repairing the defect.

The hybrid manufacturing processes for repairing metallic component combine the advantages of free-form fabrication from additive manufacturing with the high-accuracy offered by CNC machining. A Ti-6Al-4V component with a manufacturing defect was repaired by the proposed process. Compared to previous research on repairing worn components, introducing stereo vision and laser scanning dramatically simplifies the manual labor required to extract and reconstruct the defect area’s geometry.

This paper demonstrates an automated metallic component repair process by integrating stereo vision and a laser displacement sensor into a hybrid manufacturing system. Experimental results and microstructure analysis shows that the defect area could be repaired feasibly and efficiently with acceptable heat affected zone using the proposed approach.

This paper aims to summarize the influence law of hybrid deposited and micro-rolling (HDMR) technology on the bead morphology and overlapping coefficient. A better bead topology positively supports the overlapping deposited in multi-beads between layers while actively assisting the subsequent layer's deposition in the wire and arc additive manufacturing (WAAM). Hybrid-deposited and micro-rolling (HDMR) additive manufacturing (AM) technology can smooth the weld bead for improved surface quality. However, the micro-rolling process will change the weld bead profile fitting curve to affect the overlapping coefficient.

Weld bead contours for WAAM and HDMR were extracted using line lasers. A comparison of bead profile curves was conducted to determine the influence law of micro-zone rolling on the welding bead contour and fitting curve. Aiming at the optimized overlapping coefficient of weld bead in HDMR AM, the optimal HDMR overlapping coefficient curve was proposed which varies with the reduction based on the best surface flatness. The mathematical model for overlapping in HDMR was checked by comparing the HDMR weld bead contours under different rolling reductions.

A fitting function of the bead forming by HDMR AM was proposed based on the law of conservation of mass. The change rule of the HDMR weld bead overlapping spacing with the degree of weld bead rolling reduction was generated using the flat-top transition calculation for this model. Considering the damming-up impact of the first bead, the overlapping coefficient was examined for its effect on layer surface flatness.

Using the predicted overlapping model, the optimal overlapping coefficients for different rolling reductions can be achieved without experiments. These conclusions can encourage the development of HDMR technology.

This study aims to improve the welding quality and efficiency, and an algorithm should be designed to realize tracking space-curved fillet weld joints.

Fillet weld joints tracking based on the two wheels and the horizontal slider coordinated movement has been studied. The method of pattern recognition is used to identify the height deviation, and the analysis of the accuracy corresponding to recognizing height deviations has been researched. The proportional control algorithm is used to control the vertical and horizontal sliders movement, so fillet weld joints tracking in the height direction has been achieved. Based on wheels and vertical and horizontal sliders coordinated movement, the algorithm of space-curved fillet weld joints tracking has been researched.

Some experiments have been done, and experimental results show that the welding robot can track space-curved fillet weld joints with high accuracy and good reliability.

The welding robot can improve the welding quality and efficiency.

The welding robot can track fillet weld joints in ship panels, and it was shown that the welding robot could track space-curved fillet weld joints with high accuracy and good reliability.

The welding robot has many industrial and social applications.

There are various forms of fillet weld joints in the industry, and the fillet weld is curved in the space. Experimental results show that the welding robot can track space-curved fillet weld joints with good stability and high precision.

Development and demonstration of an autonomous, mobile welding robot capable of fabricating large‐scale customised structures.

An autonomous welding robot has been developed under the EC Framework V Growth program. The system comprises a global vision system for part location and orientation, and a robot transport vehicle (RTV) which carries a 6‐axis robot, robot controller, welding equipment, and local sensors at the welding torch. The RTV path, robot arm motion and weld process programming are performed automatically using sensors and specially customised simulation software.

The technology developed within the project was demonstrated, in November 2004, to be capable of identifying and welding large scale customised structures as found in the earth moving equipment and bridge fabrication industries.

The project demonstrated that current sensor technology is capable of being applied successfully to autonomous robots, but further developments in sensor technology are required to improve accuracy and joint access.

The NOMAD concept of autonomous mobile robots provides an alternative solution to welding mass customised structures.

This project demonstrated, for the first time, the capability of autonomous robots to weld large scale customised structures.

This paper aims to study the residual stress of deposited components which is a main issue to impede the widespread application of wire and arc additive manufacturing (WAAM). The interlayer dwell time is believed to have an effect on residual stress distributions in WAAM due to variance in heat dissipation condition. A coupled thermomechanical finite element model was established to evaluate the role of dwell time in between layers on the mechanical behavior of thin-walled components in WAAM, mainly involving thermal stress evolutions and residual stress distributions of the component and substrate.

Four interlayer dwell times including 0, 120 and 300 s and cooling to ambient temperature were selected in finite element modeling, and corresponding experiments were conducted to verify the reliability of the model.

The results show that with the interlayer dwell time, the stress cycling curves become more uniform and the interlayer stress-releasing effect is weakened. The residual stress levels on the substrate decrease with the increasing interlayer dwell time. In the outside surface of the component, the distributions of axial and longitudinal residual stress along the deposition path are the smoothest when the interlayer dwell time is cooling to ambient temperature. In the inside surface, a longer interlayer dwell time leads to an obvious decrease in the longitudinal and axial residual stress along the deposition path.

The comprehensive study of how the interlayer dwell time influences stress field of components is helpful to improve the deposition defects generated by WAAM.