Model for Developing a Feature Recogntion System for A Reconfigurable Bending Press Machine

Abstract Sheet metal products are often designed without a systematic consideration of downstream product development requirements, such as process planning, manufacturability, production scheduling and manufacturing optimization. This can often result in a lot of expensive and time consuming reworks. Consequently, it affects the quality, cost and delivery time of the product. In this paper, a framework for developing a web - based feature recognition system (FRS) has been proposed to recognise bending features on a reconfigurable bending press machine (RBPM). The research explores the current literature and design approaches used to develop feature recognition systems in the current manufacturing industries. This model will help to offer a suitable method for designing a web based feature recognition system for sheet metal bending using RBPMs. This model will be applied to feature recognition systems in other manufacturing industries. The model consists of the integrated platform system, information model, part model, geometric modelling and the feature model. The proposed models will aid the designer right at the design stage with useful design and the feature recognition system. The designer will be able to relate process technology to product design instead of specifying the geometric definition alone. Design of these models will provide a more convenient design environment and an easier way to integrate CAD/CAM activities. After developing the model the designer will be able to use the CAD software to develop patterns, interpret drawings and transfer dimensions to sheet materials and sections to meet the required specification.

[1]  Yan Yu,et al.  A methodology for design and reconfiguration of reconfigurable bending press machines (RBPMs) , 2014 .

[2]  S. S. Pande,et al.  An approach to recognize interacting features from B-Rep CAD models of prismatic machined parts using a hybrid (graph and rule based) technique , 2010, Comput. Ind..

[3]  Emad Abouel Nasr,et al.  A feature–based approach to an integrated CAD/CAPP system in sheet metal blanking dies , 2014 .

[4]  Gao Shu A SURVEY OF AUTOMATIC FEATURE RECOGNITION , 1998 .

[5]  Napsiah Ismail,et al.  Design of a Feature Recognition System for CAD/CAM Integration , 2013 .

[6]  Juneho Yi,et al.  Manufacturing feature recognition toward integration with process planning , 2001, IEEE Trans. Syst. Man Cybern. Part B.

[7]  Y G Li,et al.  Feature recognition technology for aircraft structural parts based on a holistic attribute adjacency graph , 2010 .

[8]  S. S. Pande,et al.  Automatic recognition of features from freeform surface CAD models , 2008, Comput. Aided Des..

[9]  Martín G. Marchetta,et al.  An artificial intelligence planning approach to manufacturing feature recognition , 2010, Comput. Aided Des..

[10]  JungHyun Han,et al.  Manufacturing feature recognition from solid models: a status report , 2000, IEEE Trans. Robotics Autom..

[11]  Jamaludin Mohd Taib,et al.  Recognizing features from engineering drawings without using hidden lines: A framework to link feature recognition and inspection systems , 2003 .

[12]  Anil K. Jain,et al.  Automatic feature extraction for multiview 3D face recognition , 2006, 7th International Conference on Automatic Face and Gesture Recognition (FGR06).

[13]  B. Gurumoorthy,et al.  Automatic extraction of free-form surface features (FFSFs) , 2012, Comput. Aided Des..

[14]  Ali K. Kamrani,et al.  A new methodology for extracting manufacturing features from CAD system , 2006, Comput. Ind. Eng..

[15]  B. R. Borkar,et al.  Automatic Extraction of Machining Features from Prismatic Parts using STEP for Downstream Applications , 2015 .

[16]  S. Q. Xie,et al.  A STEP-compliant process planning system for sheet metal parts , 2006, Int. J. Comput. Integr. Manuf..