Cooney, Benjamin Owen (2020) Design of a Rig for Automated tissue discrimination in beef striploin during trimming operations. [USQ Project]
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Text (Project)
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Abstract
In this project, an automated three-axis cartesian robotic positioning Rig has been designed, built, and performance tested. The test Rig is to place sensors for evaluating the location of tissue interfaces within a beef striploin primal cut. The results will inform the future approach and parameters for machine perception, where robotics will be used to carry out high value trimming tasks in production. For beef striploin, the automated discrimination of fat thickness for trimming is an important factor to achieve. An understanding of red meat industry production and literature on advances in the automated processing of natural mediums has provided a good foundation to design, build and test the machine.
Design of the Rigs, working requirements came from customer specifications, while supported by engineering models, met performance and application requirements. A full computer model was created for the detail design stage, which helped to size critical parameters and components. The Rig was then constructed systematically beginning with the mechanical structure and mechanisms. Electrical components were integrated into the second stage of the build, followed by the addition of software programming functions that were written to drive and control the Rig in testing performance and sequencing the placement of sensing devices. The system was tested for accuracy with results varying. Performance tests demonstrated sensor placement accuracy and repeatability errors of less than 2% of FSD. This is well within performance requirements.
The tested ability for simultaneous measurements was achieved in rapid succession in contrast with manual approaches. This important factor avoids errors resulting from relaxation in the meat between measurements. These coordinated characteristic measurements will be used to build models describing norms and variation of expected tissue interface position with respect to the overall size and shape of pre-processed primal. The models will form the baseline for robot path planning, guiding cutters relative to tissue interfaces. The new capability will enable automation of complex high-value industrial meat production operations.
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Statistics for this ePrint Item |
| Item Type: | USQ Project |
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| Item Status: | Live Archive |
| Faculty/School / Institute/Centre: | Historic - Faculty of Health, Engineering and Sciences - School of Mechanical and Electrical Engineering (1 Jul 2013 - 31 Dec 2021) |
| Supervisors: | Brett, Peter; Border, Fraser |
| Qualification: | Bachelor of Engineering (Honours) (Mechatronics) |
| Date Deposited: | 19 Aug 2021 06:10 |
| Last Modified: | 26 Jun 2023 03:57 |
| Uncontrolled Keywords: | robotic positioning rig; beef striploin |
| URI: | https://sear.unisq.edu.au/id/eprint/43073 |
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