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Developments in Finite Element Technology and Optimization Formulations for Sheet Metal Forming

Copyright © 2012. 32 pages.
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DOI: 10.4018/978-1-4666-0128-4.ch012
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MLA

Valente, Robertt A. F., Ricardo J. Alves de Sousa, António Andrade-Campos, Raquel de-Carvalho, Marisa P. Henriques, José I. V. Sena and João F. Caseiro. "Developments in Finite Element Technology and Optimization Formulations for Sheet Metal Forming." Computational Methods for Optimizing Manufacturing Technology: Models and Techniques. IGI Global, 2012. 287-318. Web. 2 Sep. 2014. doi:10.4018/978-1-4666-0128-4.ch012

APA

Valente, R. A., Alves de Sousa, R. J., Andrade-Campos, A., de-Carvalho, R., Henriques, M. P., Sena, J. I., & Caseiro, J. F. (2012). Developments in Finite Element Technology and Optimization Formulations for Sheet Metal Forming. In J. Davim (Ed.), Computational Methods for Optimizing Manufacturing Technology: Models and Techniques (pp. 287-318). Hershey, PA: Engineering Science Reference. doi:10.4018/978-1-4666-0128-4.ch012

Chicago

Valente, Robertt A. F., Ricardo J. Alves de Sousa, António Andrade-Campos, Raquel de-Carvalho, Marisa P. Henriques, José I. V. Sena and João F. Caseiro. "Developments in Finite Element Technology and Optimization Formulations for Sheet Metal Forming." In Computational Methods for Optimizing Manufacturing Technology: Models and Techniques, ed. J. Paulo Davim, 287-318 (2012), accessed September 02, 2014. doi:10.4018/978-1-4666-0128-4.ch012

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Abstract

This contribution aims to provide a comprehensive overview of some research developments in the field of computational mechanics and numerical simulations applied to metal forming processes. More specifically, this chapter’s goal is to encompass three main fields of research applied to plastic forming processes: (i) the development of alternative finite element formulations for the simulation of sheet metal forming processes; (ii) the development and discussion of distinct optimization procedures and formulations suitable for the characterization of constitutive parameters to be used in numerical simulations, relying on experimental result data; (iii) the study of non-conventional forming processes, particularly the case of single-point incremental forming operations. For each of these topics, a summary of the formulations and main ideas is provided, as well as a list of references for the interested reader. The main goal of this chapter is, therefore, to provide a comprehensive source of information for researchers from both academia and industrial worlds, about some recent achievements and future trends in the numerical simulation field.
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Introduction

This work deals with numerical simulation procedures based on the Finite Element Method (FEM) and its application to the plastic forming of complex metallic parts, both by conventional and less traditional manufacturing techniques.

The first part of the work focus on the development of new formulations for finite elements, suitable for application in sheet metal forming, and their respective implementation details. Compared to conventional displacement-based methodologies, alternative formulations, based on the Enhanced Assumed Strain (EAS) method, are presented and a new class of formulations suitable for the modelling of thin and very thin structures (metallic blanks) is described.

Aiming at the most general approach, as well as for a more realistic description of double-sided contact conditions, frequently encountered in sheet metal forming operations, “solid-shell” formulations will be presented in detail, with its advantages and drawbacks described when compared to classical solid and shell finite element formulations.

These element types resemble solid formulations, from the topology point-of-view (for instance, eight-node tri-linear brick elements), but the kinematics is based on shell formulations, taking advantages of both formulations and also benefiting from the improved performance of EAS approach, in order to avoid volumetric and thickness (transverse shear) locking effects in complex loading/boundary conditions. The suitability of the “solid-shell” formulations is even more noticeable when based on an innovative approach for the numerical integration within each finite element, that is based on a reduced in-plane integration but with a variable (user-defined) number of integration points along the thickness direction.

Doing so, it is possible to model and properly simulate metal forming operations with just one solid element layer along thickness using full 3D constitutive equations, with direct impact in lowering the computational cost of the simulations. The presented formulations are applied to typical forming operations, including anisotropic effects, of both thin and thick blanks, and also to non-conventional processes, such as the hydroforming of tubular metallic parts and single-point incremental forming of metallic blanks. Special attention is given to the ability of these enhanced formulations in predicting structural and geometrical defects during forming, such as wrinkles, thinning and springback.

The second part of this work is devoted to the development of optimization procedures to material characterization. In this sense, a set of distinct strategies will be presented in order to, starting from the knowledge of the information coming from distinct experimental mechanical essays, be able to infer and define about the optimal constitutive and hardening parameters to be used in a numerical simulation analysis. This subject is of utmost importance in the FEM, since a reliable numerical solution must derive from a suitable model and constitutive relations based on experimentally validated parameters. Within this framework, conventional optimization strategies are analyzed, and their applicability for the constitutive parameters’ determination is inferred for a number of distinct constitutive models.

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Complete Chapter List

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Table of Contents
Preface
J. Paulo Davim
Chapter 1
Pranab K. Dan, Tamal Ghosh, Sourav Sengupta
The essential problem in Cellular Manufacturing System (CMS) is to identify the machine cells and subsequent part families with an aim to curtail... Sample PDF
Application of Soft-Computing Methods in Cellular Manufacturing
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Chapter 2
M. Kanthababu
Recently evolutionary algorithms have created more interest among researchers and manufacturing engineers for solving multiple-objective problems.... Sample PDF
Multi-Objective Optimization of Manufacturing Processes Using Evolutionary Algorithms
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Chapter 3
F. Nagata, T. Yamashiro, N. Kitahara, A. Otsuka, K. Watanabe, Maki K. Habib
Multiple mobile robots with six PSD (Position Sensitive Detector) sensors are designed for experimentally evaluating the performance of two control... Sample PDF
Self Control and Server-Supervisory Control for Multiple Mobile Robots, and its Applicability to Intelligent DNC System
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Chapter 4
M. Chandrasekaran, M. Muralidhar, C. Murali Krishna, U.S. Dixit
In offline optimization of machining process with traditional or soft computing techniques, the functional relationship between the tool life and... Sample PDF
Online Machining Optimization with Continuous Learning
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Chapter 5
N. A. Fountas, A. A. Krimpenis, N. M. Vaxevanidis
Extracting CNC machining data on- or off-line demands thorough and careful planning. Exploitation of this data can be carried out by statistical... Sample PDF
Computational Techniques in Statistical Analysis and Exploitation of CNC Machining Experimental Data
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Chapter 6
V. N. Gaitonde, S. R. Karnik, J. Paulo Davim
The tungsten-copper electrodes are used in the manufacture of die steel and tungsten carbide workpieces due to high thermal and electrical... Sample PDF
Application of Particle Swarm Optimization for Achieving Desired Surface Roughness in Tungsten-Copper Alloy Machining
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Chapter 7
Shutong Xie, Zidong Zhang
Machining parameters optimization is one of the most essential and interesting problems in manufacturing world. Efficient optimization of machining... Sample PDF
Models and Optimization Techniques of Machining Parameters in Turning Operations
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Chapter 8
A.P. Markopoulos
Simulation of grinding is a topic of great interest due to the wide application of the process in modern industry. Several modeling methods have... Sample PDF
Simulation of Grinding by Means of the Finite Element Method and Artificial Neural Networks
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Chapter 9
K. Palanikumar, B. Latha, J. Paulo Davim
Glass fiber reinforced plastic (GFRP) composite materials are continuously displacing the traditional engineering materials and are finding... Sample PDF
Application of Taguchi Method with Grey Fuzzy Logic for the Optimization of Machining Parameters in Machining Composites
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Chapter 10
Alakesh Manna
In this chapter, the use of Taguchi method, Fuzzy logic, and Grey relational analysis based on an L16 (45) orthogonal array for optimizing the multi... Sample PDF
Taguchi, Fuzzy Logic and Grey Relational Analysis Based Optimization of ECSM Process during Micro Machining of E-Glass-Fibre-Epoxy Composite
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Chapter 11
Tauseef Uddin Siddiqui, Mukul Shukla
This chapter presents a detailed study of abrasive water jet (AWJ) cutting of thin and thick Kevlar fiber-reinforced polymer (FRP) composites used... Sample PDF
Modeling and Optimization of Abrasive Water Jet Cutting of Kevlar Fiber-Reinforced Polymer Composites
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Chapter 12
Robertt A. F. Valente, Ricardo J. Alves de Sousa, António Andrade-Campos, Raquel de-Carvalho, Marisa P. Henriques, José I. V. Sena, João F. Caseiro
This contribution aims to provide a comprehensive overview of some research developments in the field of computational mechanics and numerical... Sample PDF
Developments in Finite Element Technology and Optimization Formulations for Sheet Metal Forming
$37.50
Chapter 13
Luis M. M. Alves, Paulo A. F. Martins
This chapter presents an innovative forming process for joining sheet panels to tubular profiles at room temperature. Finite element analysis and... Sample PDF
Joining Sheets to Tubular Profiles by Tube Forming
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Chapter 14
R. Venkata Rao
Weld quality is greatly affected by the operating process parameters in the gas metal arc welding (GMAW) process. The quality of the welded material... Sample PDF
Modeling and Optimization of Gas Metal Arc Welding (GMAW) Process
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Chapter 15
Ilmari Juutilainen, Satu Tamminen, Juha Röning
Different industries utilize statistical prediction models that predict the product properties in process planning, control, and optimization. An... Sample PDF
A Tutorial to Developing Statistical Models for Predicting Disqualification Probability
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