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Processing Technique of Raw 3D Point Cloud Data for Accurate Reverse Engineering Exercise


Affiliations
1 Tata Technologies, MSD Building, Telco Premises, Jamshedpur-831010, Jharkhand, India
2 Department of Production Engineering and Management, Regional Institute of Technology, Jamshedpur-831014, Jharkhand, India
     

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Use of point cloud data for prototyping in Reverse Engineering (RE) is increasingly becoming popular among manufacturing communities round the globe specially, in automobile, aerospace and heavy engineering sectors where, speedy and accurate shape reproduction is the key success factor for survival in the competitive global market. This paper proposes some strategy of refining raw & noisy point cloud data, obtained from mock-up or clay-models to be used for solid or surface modeling in CAD. Discussion is limited to data acquisition methods, data viewing and validation, gap filling and homogenizing and cloud offsetting. Sample test results are presented in support of the discussed technique.
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  • Processing Technique of Raw 3D Point Cloud Data for Accurate Reverse Engineering Exercise

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Authors

Pralay Pal
Tata Technologies, MSD Building, Telco Premises, Jamshedpur-831010, Jharkhand, India
Raj Ballav
Department of Production Engineering and Management, Regional Institute of Technology, Jamshedpur-831014, Jharkhand, India
Anjani Kumar
Department of Production Engineering and Management, Regional Institute of Technology, Jamshedpur-831014, Jharkhand, India

Abstract


Use of point cloud data for prototyping in Reverse Engineering (RE) is increasingly becoming popular among manufacturing communities round the globe specially, in automobile, aerospace and heavy engineering sectors where, speedy and accurate shape reproduction is the key success factor for survival in the competitive global market. This paper proposes some strategy of refining raw & noisy point cloud data, obtained from mock-up or clay-models to be used for solid or surface modeling in CAD. Discussion is limited to data acquisition methods, data viewing and validation, gap filling and homogenizing and cloud offsetting. Sample test results are presented in support of the discussed technique.