Application of Adaptive Network Fuzzy Inference System to Die Shape Optimal Design in Sheet Metal Bending Process

碩士 === 淡江大學 === 機械與機電工程學系碩士班 === 96 === The objective of this thesis is to explore the die shape optimal design of the sheet metal bending process. Firstly, the dynamic-explicit finite element method based on the Barlat’s anisotropic yield criterion is used to simulate the sheet metal bending proces...

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Main Authors: Chih-Wei Chang, 張致緯
Other Authors: Fung-Huei Yeh
Format: Others
Language:zh-TW
Published: 2008
Online Access:http://ndltd.ncl.edu.tw/handle/97765810796794507300
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spelling ndltd-TW-096TKU054890062016-05-18T04:13:37Z http://ndltd.ncl.edu.tw/handle/97765810796794507300 Application of Adaptive Network Fuzzy Inference System to Die Shape Optimal Design in Sheet Metal Bending Process 應用適應性模糊推論系統於板金彎曲成形模具形狀最佳化設計 Chih-Wei Chang 張致緯 碩士 淡江大學 機械與機電工程學系碩士班 96 The objective of this thesis is to explore the die shape optimal design of the sheet metal bending process. Firstly, the dynamic-explicit finite element method based on the Barlat’s anisotropic yield criterion is used to simulate the sheet metal bending process in this study. After bending process, the springback angle is then analyzed by static-implicit finite element method. Besides, the die shape optimal design is performed by Adaptive Network Fuzzy Inference System (ANFIS) in various bending processes of sheet metal. In order to verify the theories, the square and V-type dies are designed for several experiments of L-bending, U-bending, and V-bending to prove the reliability of finite element analysis and optimal design by comparison of the punch load versus punch stroke relationship, the deformation history, and the springback angle after bending process between numerical and experimental results. The present study also discusses the influence of design parameters on springback angle of the bending processes. The springback angle decreases as friction coefficient or blank thickness becomes larger. The springback angle increases as bending radius or gap of dies becomes larger. Finally, this study predicts the angle of V-type die to be 85.137 degrees by ANFIS when the formed angle is 90 degrees in V-bending process of aluminum alloy sheet. A set of V-type optimal die, which angle is 85.137 degrees, is used to carry on the experiment. The formed angle is 89.93 degrees after V-bending experiment. By comparison of numerical and experimental results, it shows that the die angle of bending process can be correctly predicted by finite element method with ANFIS in the thesis. The inevitable springback problem will obtain the improvement in the sheet metal bending process. Fung-Huei Yeh 葉豐輝 2008 學位論文 ; thesis 112 zh-TW
collection NDLTD
language zh-TW
format Others
sources NDLTD
description 碩士 === 淡江大學 === 機械與機電工程學系碩士班 === 96 === The objective of this thesis is to explore the die shape optimal design of the sheet metal bending process. Firstly, the dynamic-explicit finite element method based on the Barlat’s anisotropic yield criterion is used to simulate the sheet metal bending process in this study. After bending process, the springback angle is then analyzed by static-implicit finite element method. Besides, the die shape optimal design is performed by Adaptive Network Fuzzy Inference System (ANFIS) in various bending processes of sheet metal. In order to verify the theories, the square and V-type dies are designed for several experiments of L-bending, U-bending, and V-bending to prove the reliability of finite element analysis and optimal design by comparison of the punch load versus punch stroke relationship, the deformation history, and the springback angle after bending process between numerical and experimental results. The present study also discusses the influence of design parameters on springback angle of the bending processes. The springback angle decreases as friction coefficient or blank thickness becomes larger. The springback angle increases as bending radius or gap of dies becomes larger. Finally, this study predicts the angle of V-type die to be 85.137 degrees by ANFIS when the formed angle is 90 degrees in V-bending process of aluminum alloy sheet. A set of V-type optimal die, which angle is 85.137 degrees, is used to carry on the experiment. The formed angle is 89.93 degrees after V-bending experiment. By comparison of numerical and experimental results, it shows that the die angle of bending process can be correctly predicted by finite element method with ANFIS in the thesis. The inevitable springback problem will obtain the improvement in the sheet metal bending process.
author2 Fung-Huei Yeh
author_facet Fung-Huei Yeh
Chih-Wei Chang
張致緯
author Chih-Wei Chang
張致緯
spellingShingle Chih-Wei Chang
張致緯
Application of Adaptive Network Fuzzy Inference System to Die Shape Optimal Design in Sheet Metal Bending Process
author_sort Chih-Wei Chang
title Application of Adaptive Network Fuzzy Inference System to Die Shape Optimal Design in Sheet Metal Bending Process
title_short Application of Adaptive Network Fuzzy Inference System to Die Shape Optimal Design in Sheet Metal Bending Process
title_full Application of Adaptive Network Fuzzy Inference System to Die Shape Optimal Design in Sheet Metal Bending Process
title_fullStr Application of Adaptive Network Fuzzy Inference System to Die Shape Optimal Design in Sheet Metal Bending Process
title_full_unstemmed Application of Adaptive Network Fuzzy Inference System to Die Shape Optimal Design in Sheet Metal Bending Process
title_sort application of adaptive network fuzzy inference system to die shape optimal design in sheet metal bending process
publishDate 2008
url http://ndltd.ncl.edu.tw/handle/97765810796794507300
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