Vision guided robotic inspection for parts in manufacturing and remanufacturing industry
Khan, Aamir and Mineo, Carmelo and Dobie, Gordon and MacLeod, Charles and Pierce, Gareth (2020) Vision guided robotic inspection for parts in manufacturing and remanufacturing industry. Journal of Remanufacturing, 11 (1). pp. 49-70. ISSN 2210-4690 (https://doi.org/10.1007/s13243-020-00091-x)
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Abstract
Environmental and commercial drivers are leading to a circular economy, where systems and components are routinely recycled or remanufactured. Unlike traditional manufacturing, where components typically have a high degree of tolerance, components in the remanufacturing process may have seen decades of wear, resulting in a wider variation of geometries. This makes it difficult to translate existing automation techniques to perform Non-Destructive Testing (NDT) for such components autonomously. The challenge of performing automated inspections, with off-line tool-paths developed from Computer Aided Design (CAD) models, typically arises from the fact that those paths do not have the required level of accuracy. Beside the fact that CAD models are less available for old parts, these parts often differ from their respective virtual models. This paper considers flexible automation by combining part geometry reconstruction with ultrasonic tool-path generation, to perform Ultrasonic NDT. This paper presents an approach to perform custom vision-guided ultrasonic inspection of components, which is achieved through integrating an automated vision system and a purposely developed graphic user interface with a robotic work-cell. The vision system, based on structure from motion, allows creating 3D models of the parts. Also, this work compares four different tool-paths for optimum image capture. The resulting optimum 3D models are used in a virtual twin environment of the robotic inspection cell, to enable the user to select any points of interest for ultrasonic inspection. This removes the need of offline robot path-planning and part orientation for assessing specific locations on a part, which is typically a very time-consuming phase.
ORCID iDs
Khan, Aamir, Mineo, Carmelo ORCID: https://orcid.org/0000-0002-5086-366X, Dobie, Gordon ORCID: https://orcid.org/0000-0003-3972-5917, MacLeod, Charles ORCID: https://orcid.org/0000-0003-4364-9769 and Pierce, Gareth ORCID: https://orcid.org/0000-0003-0312-8766;-
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Item type: Article ID code: 73368 Dates: DateEvent21 August 2020Published21 August 2020Published Online21 July 2020AcceptedSubjects: Technology > Manufactures Department: Faculty of Engineering > Electronic and Electrical Engineering
Strategic Research Themes > Advanced Manufacturing and Materials
Technology and Innovation Centre > Sensors and Asset ManagementDepositing user: Pure Administrator Date deposited: 29 Jul 2020 13:19 Last modified: 11 Nov 2024 12:46 URI: https://strathprints.strath.ac.uk/id/eprint/73368