Feature extraction and process planning of integrated hybrid additive-subtractive system for remanufacturing

Yufan Zheng; Rafiq Ahmad; Yufan Zheng; Rafiq Ahmad

doi:10.3934/mbe.2020373

Mathematical Biosciences and Engineering

2020, Volume 17, Issue 6: 7274-7301. doi: 10.3934/mbe.2020373

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Feature extraction and process planning of integrated hybrid additive-subtractive system for remanufacturing

Yufan Zheng ,
Rafiq Ahmad ^,

Laboratory of Intelligent Manufacturing, Design and Automation (LIMDA), Department of Mechanical Engineering, University of Alberta, Canada

Received: 21 July 2020 Accepted: 26 September 2020 Published: 23 October 2020

Discussion regarding hybrid manufacturing has dominated research in recent years. By synergistically integrating additive and subtractive manufacturing within a single workstation, the relative benefits of each manufacturing strategy are leveraged. The ability to add, remove feature flexibly enables remanufacturing end-of-life components into a "new" part with new features and functionalities. However, in the remanufacturing context, the process planning for hybrid additive-subtractive manufacturing is still an unsolved research topic. In general, a hybrid remanufacturing process is signified by an alternating sequence of additive and subtractive operations that alternatively add and remove materials on a used part, which results in a non-unique process planning. For determining an optimal sequence for hybrid remanufacturing, a quantitative evolution mechanism is demanded. Moreover, the constraints in process planning are required to be considered. For example, the collision avoidance between the workpiece and the material-dispensing nozzle is one of the most critical limitations that affect the alternating sequence. To fill the gap, automated feature extraction and cost-driven process planning method for hybrid remanufacturing are proposed in this paper. The feature extraction, developed under the level set framework, can extract optimal and collision-free additive-subtractive features. Then, the hybrid process planning task is formulated into an integer programming model with cost estimations. A case study is conducted, and the results confirm the correctness and effectiveness of the proposed method.
- remanufacturing,
- hybrid manufacturing,
- feature extraction,
- process planning
Citation: Yufan Zheng, Rafiq Ahmad. Feature extraction and process planning of integrated hybrid additive-subtractive system for remanufacturing[J]. Mathematical Biosciences and Engineering, 2020, 17(6): 7274-7301. doi: 10.3934/mbe.2020373

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Abstract

Discussion regarding hybrid manufacturing has dominated research in recent years. By synergistically integrating additive and subtractive manufacturing within a single workstation, the relative benefits of each manufacturing strategy are leveraged. The ability to add, remove feature flexibly enables remanufacturing end-of-life components into a "new" part with new features and functionalities. However, in the remanufacturing context, the process planning for hybrid additive-subtractive manufacturing is still an unsolved research topic. In general, a hybrid remanufacturing process is signified by an alternating sequence of additive and subtractive operations that alternatively add and remove materials on a used part, which results in a non-unique process planning. For determining an optimal sequence for hybrid remanufacturing, a quantitative evolution mechanism is demanded. Moreover, the constraints in process planning are required to be considered. For example, the collision avoidance between the workpiece and the material-dispensing nozzle is one of the most critical limitations that affect the alternating sequence. To fill the gap, automated feature extraction and cost-driven process planning method for hybrid remanufacturing are proposed in this paper. The feature extraction, developed under the level set framework, can extract optimal and collision-free additive-subtractive features. Then, the hybrid process planning task is formulated into an integer programming model with cost estimations. A case study is conducted, and the results confirm the correctness and effectiveness of the proposed method.

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