Automatic feature recognition using artificial neural networks to integrate design and manufacturing: Review of automatic feature recognition systems

Abstract Feature technology is considered an essential tool for integrating design and manufacturing. Automatic feature recognition (AFR) has provided the greatest contribution to fully automated computer-aided process planning system development. The objective of this paper is to review approaches based on application of artificial neural networks for solving major AFR problems. The analysis presented in this paper shows which approaches are suitable for different individual applications and how far away we are from the formation of a general AFR algorithm.

[1]  Hamid R. Parsaei,et al.  Manufacturing process planning in a concurrent design and manufacturing environment , 1996 .

[2]  Y. H. Chen,et al.  A neural network system feature recognition for two-dimensional , 1998, Int. J. Comput. Integr. Manuf..

[3]  Jung-Hong Chuang,et al.  Automatic classification of block-shaped parts based on their 2D projections , 1999 .

[4]  Yong Yue,et al.  AUTOMATED FEATURE VALIDATION FOR CREATING/EDITING FEATURE-BASED COMPONENT DATA MODELS , 1998 .

[5]  Patrick Martin,et al.  SOME ASPECTS OF INTEGRATED PRODUCT AND MANUFACTURING PROCESS , 2005 .

[6]  M. Tolouei-Rad.  An approach towards fully integration of CAD and CAM technologies , 2006 .

[7]  Mark R. Henderson,et al.  Automatic form-feature recognition using neural-network-based techniques on boundary representations of solid models , 1992, Comput. Aided Des..

[8]  George-Christopher Vosniakos,et al.  Recognizing D shape features using a neural network and heuristics , 1997, Comput. Aided Des..

[9]  S K Ong,et al.  Recognition of overlapping machining features based on hybrid artificial intelligent techniques , 2000 .

[10]  N. K. Bose,et al.  Neural Network Fundamentals with Graphs, Algorithms and Applications , 1995 .

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

[12]  Hong Yan,et al.  Object representation based on contour features and recognition by a Hopfield-Amari network , 1997, Neurocomputing.

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

[14]  Jyun-Lung Hwang.  Applying the perceptron to three-dimensional feature recognition , 1992 .

[15]  Lian Ding,et al.  Novel ANN-based feature recognition incorporating design by features , 2004, Comput. Ind..

[16]  Lian Ding,et al.  A contemporary study into the application of neural network techniques employed to automate CAD/CAM integration for die manufacture , 2009, Comput. Ind. Eng..

[17]  Jian Gao,et al.  Extraction of machining features for CAD/CAM integration , 2004 .

[18]  Ferruh Öztürk,et al.  Hybrid neural network and genetic algorithm based machining feature recognition , 2004, J. Intell. Manuf..

[19]  Zheng Bao,et al.  Neural networks and graph theory , 2008, Science in China Series F: Information Sciences.

[20]  S. S. Pande,et al.  Automatic recognition of machining features using artificial neural networks , 2009 .

[21]  Yongtae Jun,et al.  Geometric Feature Recognition for Reverse Engineering using Neural Networks , 2001 .

[22]  Saleh AMAITIK.  STEP FEATURE-BASED INTELLIGENT PROCESS PLANNING SYSTEM FOR PRISMATIC PARTS , 2004 .

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

[24]  T. N. Wong,et al.  Recognition of machining features - a hybrid approach , 2000 .

[25]  A. H. Zulkifli,et al.  Recognition of simple and complex interacting non-orthogonal features , 2002, Pattern Recognit..

[26]  Yuan-Jye Tseng.  A modular modeling approach by integrating feature recognition and feature-based design , 1999 .

[27]  Lian Ding,et al.  Study of neural network techniques for computer integrated manufacturing , 2002 .

[28]  Alan N Bramley,et al.  Advances in Integrated Design and Manufacturing in Mechanical Engineering , 2006 .

[29]  Kishore Lankalapalli,et al.  Feature recognition using ART2: a self-organizing neural network , 1997, J. Intell. Manuf..

[30]  Sri Hinduja,et al.  Extendible Classification of Design and Manufacturing Features , 2002 .

[31]  N. N. Z. Gindy,et al.  A hierarchical structure for form features , 1989 .

[32]  Sheik Meeran,et al.  Feature patterns in recognizing non-interacting and interacting primitive, circular and slanting features using a neural network , 1999 .

[33]  James A. Freeman,et al.  Simulating neural networks - with Mathematica , 1993 .

[34]  Hm Lee,et al.  A neural network system for two-dimensional feature recognition , 1998 .

[35]  Otto Willem Salomons.  Computer support in the design of mechanical products : constraint specification and satisfaction in feature based design for manufacturing , 1995 .

[36]  Godfrey C. Onwubolu.  Manufacturing features recognition using backpropagation neural networks , 1999, J. Intell. Manuf..

[37]  Jami J. Shah,et al.  A Discourse on Geometric Feature Recognition From CAD Models , 2001, J. Comput. Inf. Sci. Eng..

[38]  Zoran Miljkovic,et al.  A review of automated feature recognition with rule-based pattern recognition , 2008, Comput. Ind..

[39]  T N Wong,et al.  Automatic recognition of machining features from computer aided design part models , 2000 .

[40]  Satyandra K. Gupta,et al.  Manufacturing feature instances: which ones to recognize? , 1995, SMA '95.