Technical Briefs

FE Simulation-Based Folding Defect Prediction and Avoidance in Forging of Axially Symmetrical Flanged Components

[+] Author and Article Information
W. L. Chan, J. Lu

Department of Mechanical Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong

M. W. Fu

Department of Mechanical Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kongmmmwfu@polyu.edu.hk

J. Manuf. Sci. Eng 132(5), 054502 (Sep 10, 2010) (6 pages) doi:10.1115/1.4002188 History: Received April 02, 2009; Revised June 27, 2010; Published September 10, 2010; Online September 10, 2010

In the traditional metal forming product development paradigm, product design is generally based on heuristic know-how and experience, which are basically acquired through many years of practice. This kind of product design paradigm is of more trial-and-error than in-depth scientific calculation and analysis. Product defect prediction and quality assurance is, thus, a nontrivial issue in this product development paradigm. With the aid of finite element (FE) simulation, deformation-related defects can be predicted and analyzed. In this paper, flow-induced folding defect in forging of axially symmetrical flanged components is systematically investigated. A FE model to study the root-cause of the defect based on the material flow behavior is developed and a defect formation mechanism is revealed. The variation of material flow behavior with the changes of part geometry parameters is investigated extensively. Based on the simulation results, the parameter variation characteristics and the sensitivity of each parameter to folding defect avoidance are identified. Using industrial components as case studies, the efficiency of the proposed defect avoidance approach is verified. The approach is further proven to be able to provide practical guidelines for the design of defect-free axially symmetrical flanged components.

Copyright © 2010 by American Society of Mechanical Engineers
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Figure 1

Simulation of the folding defect formation

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Figure 2

The adjustment of tooling contour

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Figure 3

Quantification of the parameter change

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Figure 4

Case study parts

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Figure 5

The simulation result of defect formation

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Figure 6

Correlation of the studied geometry parameters with the flanged features

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Figure 7

The minimum variation of each parameter and the corresponding material flow behavior (the white broken lines indicate the original tooling geometry design)

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Figure 8

Comparison of the parameter variation in folding defect avoidance




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