A hybrid and adaptive tool-path generation approach of rapid prototyping and manufacturing for biomedical models

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Title: A hybrid and adaptive tool-path generation approach of rapid prototyping and manufacturing for biomedical models
Authors: Jin, G.Q.1, Li, W.D.1 weidong.li@coventry.ac.uk, Gao, L.2, Popplewell, K.1
Source: Computers in Industry. Apr2013, Vol. 64 Issue 3, p336-349. 14p.
Subjects: Rapid prototyping, Machine tool path, Biomedical engineering, Mathematical models, Manufacturing processes, Algorithms, Performance evaluation, Robust control
Abstract: Abstract: In this paper, a hybrid and adaptive tool-path generation approach, which is able to improve geometrical accuracy and build time of rapid prototyping/manufacturing (RP/M) for complex biomedical models, is presented. Firstly, NURBS (Non-Uniform Rational B-Spline)-based curves were introduced to represent the boundary contours of sliced layers to keep the high-fidelity information of original models. Secondly, a hybrid tool-path generation algorithm was then developed to generate contour and zigzag tool-paths. The contour tool-paths are used to fabricate the boundary and neighbouring regions of each sliced layer to preserve geometrical accuracy, and zigzag tool-paths for the internal region of the layer to simplify computing processes and speed up fabrication. Thirdly, based on developed build time and geometrical accuracy analysis models, algorithms were designed to generate an adaptive speed of the RP/M''s nozzle/print head for the contour tool-paths to address the geometrical characteristics of each layer, and to identify the best slope degree of the zigzag tool-paths towards achieving the minimum build time. Finally, five case studies of biomedical models with different geometrical characteristics and complexity were used to verify and demonstrate the improved performance of the approach in terms of processing effectiveness, geometrical accuracy and algorithm robustness. [Copyright &y& Elsevier]
Copyright of Computers in Industry is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: A hybrid and adaptive tool-path generation approach of rapid prototyping and manufacturing for biomedical models
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  Data: <searchLink fieldCode="JN" term="%22Computers+in+Industry%22">Computers in Industry</searchLink>. Apr2013, Vol. 64 Issue 3, p336-349. 14p.
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  Data: Abstract: In this paper, a hybrid and adaptive tool-path generation approach, which is able to improve geometrical accuracy and build time of rapid prototyping/manufacturing (RP/M) for complex biomedical models, is presented. Firstly, NURBS (Non-Uniform Rational B-Spline)-based curves were introduced to represent the boundary contours of sliced layers to keep the high-fidelity information of original models. Secondly, a hybrid tool-path generation algorithm was then developed to generate contour and zigzag tool-paths. The contour tool-paths are used to fabricate the boundary and neighbouring regions of each sliced layer to preserve geometrical accuracy, and zigzag tool-paths for the internal region of the layer to simplify computing processes and speed up fabrication. Thirdly, based on developed build time and geometrical accuracy analysis models, algorithms were designed to generate an adaptive speed of the RP/M''s nozzle/print head for the contour tool-paths to address the geometrical characteristics of each layer, and to identify the best slope degree of the zigzag tool-paths towards achieving the minimum build time. Finally, five case studies of biomedical models with different geometrical characteristics and complexity were used to verify and demonstrate the improved performance of the approach in terms of processing effectiveness, geometrical accuracy and algorithm robustness. [Copyright &y& Elsevier]
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  Data: <i>Copyright of Computers in Industry is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.compind.2012.12.003
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        Text: English
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      – SubjectFull: Biomedical engineering
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      – SubjectFull: Performance evaluation
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              Text: Apr2013
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              Y: 2013
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