Volume decomposition of CAD models for rapid prototyping technology

Purpose – This paper reports on the work done to decompose a large sized solid model into smaller solid components for rapid prototyping technology. The target geometric domain of the solid model includes quadrics and free form surfaces.Design/methodology/approach – The decomposition criteria are based on the manufacturability of the model against a user‐defined manufacturing chamber size and the maintenance of geometrical information of the model. In the proposed algorithm, two types of manufacturing chamber are considered: cylindrical shape and rectangular shape. These two types of chamber shape are commonly implemented in rapid prototyping machines.Findings – The proposed method uses a combination of the regular decomposition (RD)‐method and irregular decomposition (ID)‐method to split a non‐producible solid model into smaller producible subparts. In the ID‐method, the producible feature group decomposition (PFGD)‐method focuses on the decomposition by recognising producible feature groups. In the deco...

[1]  Sheik Meeran,et al.  Recognition and interpretation of interacting and non-interacting features using spatial decomposition and Hamiltonian path search , 1996 .

[2]  Ferruh Öztürk,et al.  Neural network based non-standard feature recognition to integrate CAD and CAM , 2001, Comput. Ind..

[3]  Ralph R. Martin,et al.  Putting objects into boxes , 1988 .

[4]  Jami J. Shah,et al.  Automatic recognition of interacting machining features based on minimal condition subgraph , 1998, Comput. Aided Des..

[5]  S. H. Chuang,et al.  Three-dimensional shape pattern recognition using vertex classification and vertex-edge graphs , 1990, Comput. Aided Des..

[6]  Andrew S. Glassner,et al.  An introduction to ray tracing , 1989 .

[7]  Rajit Gadh,et al.  Shape feature determination usiang the curvature region representation , 1997, SMA '97.

[8]  James Arvo,et al.  A survey of ray tracing acceleration techniques , 1989 .

[9]  K. Tang,et al.  Algorithmic aspects of alternating sum of volumes. Part 1: Data structure and difference operation , 1991, Comput. Aided Des..

[10]  T. C. Chang,et al.  Graph-based heuristics for recognition of machined features from a 3D solid model , 1988 .

[11]  Barry Joe,et al.  Reparameterization of rational triangular Bézier surfaces , 1994, Comput. Aided Geom. Des..

[12]  Li Lin,et al.  Rule-based automatic part feature extraction and recognition from CAD data , 1992 .

[13]  Jami J. Shah Assessment of features technology , 1991, Comput. Aided Des..

[14]  Sheik Meeran,et al.  Decomposition of interacting features using a Kohonen self-organizing feature map neural network , 1999 .

[15]  Hiroshi Sakurai,et al.  Volume decomposition and feature recognition: part 1 - polyhedral objects , 1995, Comput. Aided Des..

[16]  Arno Formella,et al.  Ray-tracing acceleration techniques , 2000 .

[17]  Beno Benhabib,et al.  Geometric reasoning for the extraction of form features , 1996, Comput. Aided Des..

[18]  T. C. Woo,et al.  Spherical Maps: Their Construction, Properties, and Approximation , 1994 .

[19]  Charles L. Thomas,et al.  Rapid prototyping of large scale aerospace structures , 1996, 1996 IEEE Aerospace Applications Conference. Proceedings.

[20]  Rajit Gadh,et al.  MMCs and PPCs as constructs of curvature regions for form feature determination , 1998, Comput. Aided Des..

[21]  Chi-keung Chan,et al.  Minimum bounding boxes and volume decomposition of CAD models , 2003 .

[22]  Shuo-Yan Chou,et al.  Parting directions for mould and die design , 1993, Comput. Aided Des..

[23]  Chun Liu,et al.  Extraction of manufacturing details from geometric models , 1985 .

[24]  JungHyun Han,et al.  Hint-based reasoning for feature recognition: status report , 1998, Comput. Aided Des..

[25]  Yong Se Kim,et al.  Recognition of form features using convex decomposition , 1992, Comput. Aided Des..

[26]  David C. Anderson,et al.  Fast feature extraction for machining applications , 1994, Comput. Aided Des..

[27]  Robert Sowerby,et al.  Feature extraction of concave and convex regions and their intersections , 1993, Comput. Aided Des..

[28]  Martti Mäntylä,et al.  Feature modelling by incremental feature recognition , 1993, Comput. Aided Des..

[29]  C. Chan,et al.  Determination of the minimum bounding box of an arbitrary solid: an iterative approach , 2001 .

[30]  Leila De Floriani,et al.  Geometric modeling of solid objects by using a face adjacency graph representation , 1985, SIGGRAPH.

[31]  Yong Se Kim,et al.  A Convex Decomposition Using Convex Hulls and Local Cause of Its Non-Convergence , 1992 .

[32]  Timothy J. Tautges,et al.  Feature based hex meshing methodology: feature recognition and volume decomposition , 2001, Comput. Aided Des..

[33]  Les A. Piegl,et al.  The NURBS Book , 1995, Monographs in Visual Communication.

[34]  Yong Se Kim,et al.  Geometric reasoning for machining features using convex decomposition , 1993, Comput. Aided Des..

[35]  Kwangsoo Kim,et al.  A feature-based approach to extracting machining features , 1998, Comput. Aided Des..

[36]  Woojin Chung,et al.  Design of the chained form manipulator , 1997, Proceedings of International Conference on Robotics and Automation.

[37]  Sooi-Thor Tan,et al.  Generating assembly features onto split solid models , 2003, Comput. Aided Des..

[38]  David W. Rosen,et al.  Special panel session for feature recognition at the 1997 ASME Computers in Engineering Conference , 1998, Comput. Aided Des..

[39]  Dinesh Manocha,et al.  OBBTree: a hierarchical structure for rapid interference detection , 1996, SIGGRAPH.

[40]  Joseph O'Rourke,et al.  Finding minimal enclosing boxes , 1985, International Journal of Computer & Information Sciences.