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2017 | OriginalPaper | Chapter

Feature Extraction and Manufacturability Assessment of Sheet Metal Parts

Authors : Shailendra Kumar, Rajender Singh, Deepak Panghal, Sachin Salunkhe, Hussein M. A. Hussein

Published in: AI Applications in Sheet Metal Forming

Publisher: Springer Singapore

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Abstract

To automate the process of die design, firstly all design features of sheet metal parts are to be extracted automatically from drawing files by a computer-aided system. After feature extraction, next important activity is manufacturability assessment of sheet metal parts. Traditional process of manufacturability assessment of sheet metal parts involves calculations and decisions, which have to be made on the basis of experience and practice codes without the computer aids. In the present chapter, an automatic feature recognition system is described. The system initially extracts the basic entities from the 3-D CAD model and recognizes various design features of flat parts, bending parts, and deep drawn parts. The system is coded in AutoLISP language. The system displays the details of all design features of part in the prompt area of AutoCAD software. The system has been installed on Autodesk AutoCAD software. The present chapter also describes a knowledge-based system (KBS) for manufacturability assessment of sheet metal parts. Knowledge obtained from published literature, die designers, and process planners has been analyzed, tabulated, and incorporated into a set of production rules of the IF–THEN variety. The system is coded in the AutoLISP language and user interface is developed using visual basic (VB). The system output includes recommendations on the suitability of design features of the part for required manufacturing operations. The knowledge base of this system can be modified depending upon the capabilities of a specific shop floor. The low cost of the system makes it affordable for process planners working in small-and medium-size sheet metal industries.

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Metadata
Title
Feature Extraction and Manufacturability Assessment of Sheet Metal Parts
Authors
Shailendra Kumar
Rajender Singh
Deepak Panghal
Sachin Salunkhe
Hussein M. A. Hussein
Copyright Year
2017
Publisher
Springer Singapore
DOI
https://doi.org/10.1007/978-981-10-2251-7_3

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