A reverse engineering methodology for rotary components from point cloud data

This paper presents data analysis and model generation techniques for reverse engineering rotary components such as shafts and rotary dies. Existing reverse engineering techniques create a computer-aided design model from point cloud data that are a mathematical ‘best fit’, but this may be an inaccurate representation due to noise contained in the model. Also, rotary components have their own set of design parameters and reverse engineering design challenges. For several rotary applications, the point cloud data go through a series of transformations (such as transforming the points from a rotational to a planar representation) in order to extract the relevant information, and then a ‘healing’ process is performed to modify critical geometry and dimensions. To meet these challenges, a systematic approach is adopted in a comprehensive manner to extract the relevant information and transform it into relevant design knowledge. Several practical examples are presented that highlight the issues, the reverse engineering methodology, and how these techniques provide a platform for any subsequent design modifications and the component manufacture.

[1]  Andrew W. Fitzgibbon,et al.  Direct Least Square Fitting of Ellipses , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  B. Logar,et al.  Feature-Based Part Database Design and Automatic Forming of Part Families for GT , 1991 .

[3]  Brent Stucker,et al.  A finish machining strategy for rapid manufactured parts and tools , 2003 .

[4]  Piotr Breitkopf,et al.  Improving surface meshing from discrete data by feature recognition , 2004, Engineering with Computers.

[5]  Hoda A. ElMaraghy,et al.  Allocation of Geometric Tolerances: New Criterion and Methodology , 1997 .

[6]  J. Y. Zhu,et al.  Piecewise B-spline Surfaces Fitting to Arbitrary Triangle Meshes , 2002 .

[7]  Nikolai I. Chernov,et al.  Least squares fitting of circles and lines , 2003, ArXiv.

[8]  Anath Fischer,et al.  Surface Reconstruction of freeform Objects Based on Hierarchical Space Decomposition , 2003, Int. J. Shape Model..

[9]  Wang Hai-bin,et al.  Research on integrated reverse engineering technology for forming sheet metal with a freeform surface , 2001 .

[10]  Yin Zhongwei,et al.  Automatic segmentation and approximation of digitized data for reverse engineering , 2003 .

[11]  Brent Stucker,et al.  Circular hole recognition for STL‐based toolpath generation , 2005 .

[12]  Nikolai I. Chernov,et al.  Least Squares Fitting of Circles , 2005, Journal of Mathematical Imaging and Vision.

[13]  K. Case,et al.  Feature-based representation for manufacturing planning , 2000 .

[14]  Robert B. Fisher.  Applying knowledge to reverse engineering problems , 2004, Comput. Aided Des..

[15]  H. ElMaraghy,et al.  Curve and Surface Modeling with Uncertainties Using Dual Kriging , 1999 .

[16]  John E. Freund,et al.  Probability and statistics for engineers , 1965 .

[17]  S Park,et al.  Automated segmentation of point data in a feature-based reverse engineering system , 2002 .

[18]  Jindong Chen,et al.  Automatic Reconstruction of 3D CAD Models from Digital Scans , 1999, Int. J. Comput. Geom. Appl..

[19]  Tyson R. Browning,et al.  Applying the design structure matrix to system decomposition and integration problems: a review and new directions , 2001, IEEE Trans. Engineering Management.

[20]  Hoda A. ElMaraghy,et al.  Data Fitting Using Dual Kriging and Genetic Algorithms , 1996 .

[21]  Anath Fischer,et al.  3D scanning and level of detail modelling for design and manufacturing , 1998 .

[22]  John A. Schey,et al.  Introduction to manufacturing processes , 1977 .

[23]  Alan V. Oppenheim,et al.  Discrete-time signal processing (2nd ed.) , 1999 .

[24]  J. Peklenik,et al.  Computer-Aided Design of the Part Spectrum Data Base and Its Application to Design and Production , 1982 .

[25]  Anath Fischer,et al.  Modeling in Reverse Engineering for Injection Molding Analysis of 3D Thin Objects , 1997 .

[26]  Saeid Motavalli.  Review of reverse engineering approaches , 1998 .

[27]  R. Jill Urbanic.  A systematic design recovery framework for mechanical components. , 2006 .

[28]  Thomas C. Henderson,et al.  Feature-based reverse engineering of mechanical parts , 1999, IEEE Trans. Robotics Autom..

[29]  Marco Attene,et al.  Automatic Surface Reconstruction from Point Sets in Space , 2000, Comput. Graph. Forum.

[30]  Hoda A. ElMaraghy,et al.  An Integrated Systematic Design Recovery Framework , 2006, J. Comput. Inf. Sci. Eng..

[31]  Chia-Hsiang Menq,et al.  Automatic data segmentation for geometric feature extraction from unorganized 3-D coordinate points , 2001, IEEE Trans. Robotics Autom..

[32]  Jean-Pierre Kruth,et al.  Reverse engineering modelling of free-form surfaces from point clouds subject to boundary conditions , 1998 .

[33]  Li Lin,et al.  A knowledge-based design critique system for manufacture and assembly of rotational machined parts in concurrent engineering , 1996 .

[34]  H. H. Ryffel.  Machinery's Handbook , 1984 .

[35]  Alan V. Oppenheim,et al.  Discrete-Time Signal Pro-cessing , 1989 .

[36]  Anath Fischer,et al.  Reconstruction of Freeform Objects with Arbitrary Topology Using Neural Networks and Subdivision Techniques , 2003 .

[37]  Arthur G. Erdman,et al.  Mechanism Design : Analysis and Synthesis , 1984 .