Browsing by Author "Michel, Florent"

Now showing 1 - 6 of 6
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    Compensation strategies for robotic motion errors for additive manufacturing (AM)
    (University of Texas, 2016-08-10) Bandari, Yashwanth K.; Charrett, Thomas O. H.; Michel, Florent; Ding, Jialuo; Williams, Stewart W.; Tatum, Ralph P.
    It is desirable to utilise a robotic approach in additive manufacturing as Computer Numerical Control (CNC) is expensive and it has high maintenance costs. A robotic approach is relatively inexpensive compared to CNC and can provide much more flexibility, enabling a variety of configurations and easier parallel processing. However, robots struggle to achieve high positioning accuracy and are more prone to disturbances from the process forces. This paper attempts to characterise the robot position and velocity errors, which depend on the build strategy deployed, using a laser speckle correlation sensor to measure the robotic motion. An assessment has been done as to whether these errors would cause any problem in additive manufacturing techniques, where the test parts were built using the Wire+Arc Additive Manufacture (WAAM) technique. Finally, different compensation strategies are discussed to counter the robotic errors and a reduction of 3 mm in top surface profile irregularity by varying the wire feed speed (WFS) during the path has been demonstrated.
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    Investigation of a path planning solution for wire + arc additive manufacture.
    (Cranfield University, 2018-12) Michel, Florent; Lockett, Helen L.; Ding, Jialuo
    Wire + Arc Additive Manufacturing (WAAM) has become a crucial asset for industrial manufacturing in the field of medium to large metallic deposition thanks to its high-rate deposition of various metals, its low-cost equipment and a potentially unlimited build volume. A key element for commercial deployment is to develop an intuitive path planning software, which can determine the optimal deposition strategy, whilst respecting WAAM’s constraints inherent to arc welding deposition. Traditional approaches to additive manufacturing path planning are often derived from CNC machining, but these strategies are incompatible with some fundamental characteristics of WAAM. For this reason, the present work aims to investigate a path planning solution entirely focused on the WAAM requirements. The architecture of a Path Generator Framework for WAAM is, thus, first introduced to offer complete freedom of path planning development all along this study. To validate the developed framework, a feature- based approach is presented: this allows the fast and efficient deployment of the WAAM technology for a limited range of geometric features and sets up the basis of path planning for WAAM. Then, a more flexible solution called Modular Path Planning is introduced to incorporate the modularity of feature-based design into the traditional layer-by-layer build strategy. By assisting the user in dividing each layer into individual deposition sections, this method enables users to adapt the path strategy to the targeted geometry allowing the construction of a wide variety of complex geometries. Finally, a deep learning solution called DeepWAAM is proposed to reach, in the future, a fully automated path planning solution for WAAM by automatically dividing build layers into deposition sections with no need for user intervention.
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    Laser speckle velocimetry for robot manufacturing
    (Cranfield University, 2017-07-04 15:10) Charrett, Tom; Bandari, Yashwanth K.; Michel, Florent; Ding, Jialuo; Williams, Stewart; Tatam, Ralph
    Data files associated with SPIE Optical Metrology, Munich 2017 paper: Thomas O. H. Charrett ; Yashwanth K. Bandari ; Florent Michel ; Jialuo Ding ; Stewart W. Williams ; Ralph P. Tatam; Laser speckle velocimetry for robot manufacturing . Proc. SPIE 10329, Optical Measurement Systems for Industrial Inspection X, 103291Z (June 26, 2017); doi:10.1117/12.2269989
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    Laser speckle velocimetry for robot manufacturing
    (SPIE, 2017-06-26) Charrett, Thomas O. H.; Bandari, Yashwanth K.; Michel, Florent; Ding, Jialuo; Williams, Stewart W.; Tatum, Ralph P.
    A non-contact speckle correlation sensor for the measurement of robotic tool speed is presented for use in robotic manufacturing and is capable of measuring the in-plane relative velocities between a robot end-effector and the workpiece or other surface. The sensor performance was assessed in the laboratory with the sensor accuracies found to be better than 0:01 mm/s over a 70 mm/s velocity range. Finally an example of the sensors application to robotic manufacturing is presented where the sensor was applied to tool speed measurement for path planning in the wire and arc additive manufacturing process using a KUKA KR150 L110/2 industrial robot.
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    A modular path planning solution for Wire + Arc Additive Manufacturing
    (Elsevier, 2019-05-11) Michel, Florent; Lockett, Helen L.; Ding, Jialuo; Martina, Filomeno; Marinelli, Gianrocco; Williams, Stewart W.
    Wire + Arc Additive Manufacturing (WAAM) has proven its capability to build medium to large metallic parts thanks to its high-rate deposition and its potentially unlimited build volume. Moreover, the low-cost equipment and the ability to deposit various metals make WAAM a strong candidate to become a standard industrial process. However, like all Additive Manufacturing (AM) technologies, the key to manufacturing suitable parts lies in the generation of an optimised path that guarantees a uniform defect-free deposition. Most AM technologies have been able to use traditional path strategies derived from CNC machining, but the specificities inherent to the arc deposition make the use of those solutions unreliable across a variety of topologies. Nevertheless, studies have shown that superior results can be achieved by using a feature-based design approach, but developing a path strategy for each new geometry would be a very time-consuming task. Therefore, this paper introduces the Modular Path Planning (MPP) solution that aims to incorporate the modularity of feature-based design into the traditional layer-by-layer strategy. By dividing each layer into individual deposition sections, this method allows users to adapt the path planning to the targeted geometry allowing the construction of a wide variety of complex geometries. This paper also proposes a software implementation that limits user interventions and reduces user inputs to basic CAD modelling operations. Moreover, the MPP has been compared to a traditional path planning solution and used to build a complex part for industry.
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    A non-contact laser speckle sensor for the measurement of robotic tool speed
    (Elsevier, 2018-04-23) Charrett, Thomas O. H.; Bandari, Yashwanth K.; Michel, Florent; Ding, Jialuo; Williams, Stewart W.; Tatam, Ralph P.
    A non-contact speckle correlation sensor for the measurement of robotic tool speed is described that is capable of measuring the in-plane relative velocities between a robot end-effector and the workplace or other surface. The sensor performance has been assessed in the laboratory with sensor accuracies of ±0.01 mm/s over a ±70 mm/s velocity range. The effect of misalignment of the sensor on the robot was assessed for variation in both working distance and angular alignment with sensor accuracy maintained to within 0.025 mm/s (<0.04%) over a working distance variation of ±5 mm from the sensor design distance and ±0.4 mm/s (0.6%) for a misalignment of 5°. The sensor precision was found to be limited by the peak fitting accuracy used in the signal processing with peak errors of ±0.34 mm/s. Finally an example of the sensor’s application to robotic manufacturing is presented where the sensor was applied to tool speed measurement for path planning in the wire and arc additive manufacturing process using a KUKA KR150 L110/2 industrial robot.