Establishing a knowledge graph-based recommendation system for product family reconfiguration and redesign for a robotics-based use case
This research investigates the integration of modular product design with generative design to enhance the reconfiguration and redesign of robotic arms within various industrial applications. By leveraging a knowledge graph-based system, this study aims to facilitate rapid and precise modificatio...
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| 格式: | Final Year Project |
| 語言: | English |
| 出版: |
Nanyang Technological University
2024
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| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/177394 |
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| 機構: | Nanyang Technological University |
| 語言: | English |
| 總結: | This research investigates the integration of modular product design with generative
design to enhance the reconfiguration and redesign of robotic arms within various industrial
applications. By leveraging a knowledge graph-based system, this study aims to facilitate rapid
and precise modifications of robotic arms to meet specific customer needs without having to
create new products from the ground-up. A case study in the Electronics Industry is created
utilizing the Openmanipulator-X robotic arm to illustrate the implementation of this hybrid
system. The methodology adopted involves constructing a comprehensive knowledge graph that
encapsulates customer preferences, component relationships, and engineering constraints,
allowing for efficient recommendation, and prototyping of reconfigured robotic arms with
optimized generative designs for unmatched modules from the knowledge-graph based
reconfiguration approach. This approach promises to minimize production costs and time while
maximizing the adaptability and efficacy of robotic manufacturing systems. |
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