Wire Arc Additive Manufacturing (WAAM) is attracting significant attention in industry and academia due to its ability to capture the benefits of additive manufacturing for production of large components of medium geometric complexity. Uniquely, WAAM combines the use of wire and electric arc as a fusion source to build components in a layer-by-layer approach, both of which can offer significant cost savings compared to powder and alternative fusion sources, such as laser and electron beam, respectively. Meanwhile, a high deposition rate, key for producing such components, is provided, whilst also allowing significant material savings compared to conventional manufacturing processes. However, high quality production in a wide range of materials is limited by the elevated levels of heat input which causes a number of materials processing challenges in WAAM. The materials processing challenges are fully identified in this paper to include the development of high residual stresses, undesirable microstructures, and solute segregation and phase transformations at solidification. The thermal profile during the build poses another challenge leading to heterogeneous and anisotropic material properties. This paper outlines how the materials processing challenges may be addressed in WAAM by implementation of quality improving ancillary processes. The primary WAAM process selections and ancillary processes are classified by the authors and a comprehensive review of their application conducted. Strategies by which the ancillary processes can enhance the quality of WAAM parts are presented. The efficacy and suitability of these strategies for versatile and cost effective WAAM production are discussed and a future vision of WAAM process developments provided.

https://purehost.bath.ac.uk/ws/files/183236429/StrategiesAndProcessesForHighQualityWireArcAdditiveManufacturing_Manuscript.pdf

Invited review article: Strategies and processes for high quality wire arc additive manufacturing

Early studies on robot machining were reported in the 1990s. Even though there are continuous worldwide researches on robot machining ever since, the potential of robot applications in machining has yet to be realized. In this paper, the authors will first look into recent development of robot machining. Such development can be roughly categorized into researches on robot machining system development, robot machining path planning, vibration/chatter analysis including path tracking and compensation, dynamic, or stiffness modeling. These researches will obviously improve the accuracy and efficiency of robot machining and provide useful references for developing robot machining systems for tasks once thought to only be capable by CNC machines. In order to advance the technology of robot machining to the next level so that more practical and competitive systems could be developed, the authors suggest that future researches on robot machining should also focus on robot machining efficiency analysis, stiffness map-based path planning, robotic arm link optimization, planning, and scheduling for a line of machining robots.

https://link.springer.com/content/pdf/10.1007%2Fs00170-012-4433-4.pdf

Robot machining: recent development and future research issues

In the factory of the future, most of the operations will be done by autonomous robots that need visual feedback to move around the working space avoiding obstacles, to work collaboratively with humans, to identify and locate the working parts, to complete the information provided by other sensors to improve their positioning accuracy, etc. Different vision techniques, such as photogrammetry, stereo vision, structured light, time of flight and laser triangulation, among others, are widely used for inspection and quality control processes in the industry and now for robot guidance. Choosing which type of vision system to use is highly dependent on the parts that need to be located or measured. Thus, in this paper a comparative review of different machine vision techniques for robot guidance is presented. This work analyzes accuracy, range and weight of the sensors, safety, processing time and environmental influences. Researchers and developers can take it as a background information for their future works.

/pdf/robot-guidance-using-machine-vision-techniques-in-industrial-zuoh42kwwj.pdf

Robot Guidance Using Machine Vision Techniques in Industrial Environments: A Comparative Review

Robots in machining

For the past three decades, robotic machining has attracted a large amount of research interest owning to the benefit of cost efficiency, high flexibility and multi-functionality of industrial robot. Covering articles published on the subjects of robotic machining in the past 30 years or so; this paper aims to provide an up-to-date review of robotic machining research works, a critical analysis of publications that publish the research works, and an understanding of the future directions in the field. The research works are organised into two operation categories, low material removal rate (MRR) and high MRR, according their machining properties, and the research topics are reviewed and highlighted separately. Then, a set of statistical analysis is carried out in terms of published years and countries. Towards an applicable robotic machining, the future trends and key research points are identified at the end of this paper.

/pdf/industrial-robotic-machining-a-review-22ic1kzvyl.pdf

Industrial robotic machining: a review

Although robots tend to be as competitive as CNC machines for some operations, they are not yet widely used for machining operations. This may be due to the lack of certain technical information that is required for satisfactory machining operation. For instance, it is very difficult to get information about the stiffness of industrial robots from robot manufacturers. As a consequence, this paper introduces a robust and fast procedure that can be used to identify the joint stiffness values of any six-revolute serial robot. This procedure aims to evaluate joint stiffness values considering both translational and rotational displacements of the robot end-effector for a given applied wrench (force and torque). In this paper, the links of the robot are assumed to be much stiffer than its actuated joints. The robustness of the identification method and the sensitivity of the results to measurement errors and the number of experimental tests are also analyzed. Finally, the actual Cartesian stiffness matrix of the robot is obtained from the joint stiffness values and can be used for motion planning and to optimize machining operations.

/pdf/joint-stiffness-identification-of-six-revolute-industrial-2t16t593fm.pdf

Joint stiffness identification of six-revolute industrial serial robots

This paper presents a new methodology for the joint stiffness identification of industrial serial robots and as consequence for the evaluation of both translational and rotational displacements of the robot's end-effector subject to an external wrench (force and torque). In this paper, the robot's links are supposed to be quite stiffer than the actuated joints as it is usually the case with industrial serial robots. The robustness of the identification method and the sensitivity of the results to measurement errors, and the number of experimental tests are also analyzed. The Kuka KR240-2 robot is used as an illustrative example throughout the paper.

/pdf/joint-stiffness-identification-of-industrial-serial-robots-2zqlve6a7g.pdf

Joint stiffness identification of industrial serial robots

This paper presents a new methodology for joint stiffness identification of serial robots. This methodology aims at evaluating all joint stiffness values responsible for both translational and rotational displacements of the robot end-effector subject to an external wrench (force and torque). The links of the robot are supposed to be quite stiffer than the joints and not known as it is usually the case with industrial serial robots. The robustness of the identification method and the sensitivity of the results to measurement errors and number of experimental tests are also analyzed. The Kuka KR240-2 robot is used as an illustrative example through the paper.

A methodology for joint stiffness identification of serial robots

The paper focuses on the stiffness modeling of heavy industrial robots with gravity compensators. The main attention is paid to the identification of geometrical and elastostatic parameters and calibration accuracy. To reduce impact of the measurement errors, the set of manipulator configurations for calibration experiments is optimized with respect to the proposed performance measure related to the end-effector position accuracy. Experimental results are presented that illustrate the advantages of the developed technique.

https://hal.archives-ouvertes.fr/hal-00909578/document

Claire Dumas

Papers

Joint stiffness identification of six-revolute industrial serial robots

Joint stiffness identification of industrial serial robots

A methodology for joint stiffness identification of serial robots

Identification of geometrical and elastostatic parameters of heavy industrial robots

Identification of geometrical and elastostatic parameters of heavy industrial robots