Machining and forming technologies Volume 2 / J. Paulo Davim, editor.

Format:

Book

Contributor:

Davim, J. Paulo.

Series:

Machining and Forming Technologies

Machining and forming technologies, 2157-250X ; v. 2

Language:

English

Subjects (All):

Manufacturing processes.

Machining.

Production engineering.

Physical Description:

1 online resource (359 p.)

Edition:

1st ed.

Place of Publication:

New York : Nova Science Publishers, Inc., c2011.

Language Note:

English

Summary:

Machining and forming technologies are two of the most important manufacturing processes, which includes a large group of manufacturing processes in which plastic deformation and other techniques are used to change the shape of workpieces.

Contents:

Intro

MACHINING AND FORMING TECHNOLOGIES VOLUME 2

CONTENTS

PREFACE

Chapter 1 THERMAL MODELLING OF MATERIAL REMOVAL RATE AND SURFACE ROUGHNESS IN DIE SINKING-ELECTRO CHEMICAL SPARK MACHINING PROCESS

ABSTRACT

1. INTRODUCTION

2. MODELING FOR TEMPERATURE FIELD IN HEAT AFFECTED ZONE OF A SINGLE SPARK

2.1. Governing Equation, Initial and Boundary Conditions

2.2. Finite Element Formulation

3. MODELLING FOR MRR AND ASR

3.1. Material Removal Rate (MRR)

3.2. Average Surface Roughness (ASR)

4. RESULTS AND DISCUSSION

4.1. Comparison of MRR

4.2. Computational Experiments

Energy Partition (Fw)

Spark Radius ()

4.3. Parametric Studies

Effect of Energy Partition

Effect of Duty Factor

Effect of Spark Radius

Effect of Electrolyte Concentration

CONCLUSIONS

REFERENCES

Chapter 2 PREDICTION OF SURFACE ROUGHNESS IN ELECTRICAL DISCHARGE MACHINING OF D2 STEEL USING REGRESSION AND ARTIFICIAL NEURAL NETWORKS MODELING

2. EXPERIMENTAL DETAILS

3. SURFACE ROUGHNESS MEASUREMENT

4. PREDICTIVE MODELS FOR SURFACE ROUGHNESS

4.1. Regression Analysis

4.2. Neural Network Modeling

4.2.1. Back-Propagation Neural Network

4.2.2. Radial Basis Function Neural Network

5. RESULT AND DISCUSSION

5.1. Parametric Influences on Surface Roughness

5.1.1. Effect of Ip

5.1.2. Effect of Ton

5.2. Prediction Error

6. ANALYSIS SURFACE ROUGHNESS USING SEM

CONCLUSION

ACKNOWLEDGMENT

Chapter 3 ON THE RESPONSE SURFACE MODELLING OF WIRE ELECTRICAL DISCHARGE MACHINING OF AL/SICP METAL MATRIX COMPOSITES (MMCS)

2. MACHINING OF METAL MATRIX COMPOSITES

3. EXPERIMENTS

4. DESIGN OF EXPERIMENTS

5. RESULTS AND DISCUSSION.

5.1. Response Surface Modelling (RSM)

5.2. Influence of Process Parameters on Cutting Rate

5.3. Influence of Process Parameters on Surface Roughness

5.4. Influence of Input Process Parameters on Kerf Width

ACKNOWLEDGMENTS

Chapter 4 EXPERIMENTAL INVESTIGATION ON CBN FINISH-TURNING OF HARDENED AISI 52100 STEEL

3. ORTHOGONAL ARRAY EXPERIMENTS

3.1. Analysis of Variance

3.2. Average Responses and Optimal Conditions

3.3. Response Equations

4. EXPERIMENTS WITH SIMULATED FLANK WEAR

4.1. Effect on Surface Roughness

4.2. Effect on Tool Temperature

4.3. Effect on Tool Vibration

Chapter 5 ANALYSIS OF VIBRATION SIGNAL CHARACTERISTICS AND ITS CORRELATION WITH SURFACE ROUGHNESS IN TURNING

2. LITERATURE REVIEW

2.1. Vibration in Machining Process

2.2. Signal Processing

2.3. Surface Roughness in Machining

3. EXPERIMENTAL PROCEDURE, MATERIALS AND EQUIPMENTS

3.1. Machine Tool, Workpiece, Cutting Tool and Dampers

3.2. Cutting Tests

4. DISCUSSION OF RESULTS

4.1. Analysis of Amplitude Spectrum Signals

4.2. Surface Characterization by Probability Distribution

4.3. Surface Roughness

Chapter 6 FINITE ELEMENT ANALYSIS FOR THE EFFECTS OF FLANK WEAR AND SOME CUTTING PARAMETERS ON CUTTING STRESSES IN TURNING OF AISI 1060 STEEL

1.1. The Main Cutting Force in Turning

2. MATERIALS AND METHOD

2.1. The Cutting Tool Modelling

3. RESULTS

Chapter 7 MULTI-ATTRIBUTE OPTIMIZATION OF CNC END MILLING PROCESS PARAMETERS USING UTILITY BASED TAGUCHI PHILOSOPHY

2. INTRODUCTION TO TAGUCHI METHOD.

3. INTRODUCTION TO UTILITY CONCEPT

4. EXPERIMENTAL SETUP AND PROCEDURE

5. OPTIMIZATION OF SURFACE ROUGHNESS AND MRR IN END MILLING PROCESS

APPENDIX

Chapter 8 DMM BASED APPROACH TO PRODUCE AEROENGINE DISCS

2. MATERIAL

3. ISOTHERMAL COMPRESSION TESTING

3.1. Effect of Temperature

3.2. Effect of Strain Rate

4. DYNAMIC MATERIALS MODELING

4.1. Processing Map for IMI 834

5. NEAR ISOTHERMAL FORGING PROCESS DESIGN

6. FINITE ELEMENT ANALYSIS (FEA)

6.1. Preforming

6.2. Disc Forging

7. PROCESSING OF IMI 834

8. MECHANICAL PROPERTY EVALUATION

SUMMARY

Chapter 9 EBSD STUDIES ON THE INFLUENCE OF TEXTURE ON THE MECHANICAL PROPERTIES DEVELOPED IN WARM ROLLED DUPLEX STAINLESS STEELS

2. EXPERIMENTAL WORK

3. RESULTS AND DISCUSSION

Chapter 10 COMPREHENSIVE REVIEW ON DRILLING OF MULTIMATERIAL STACKS

2. DRILLING OF POLYMER MATRIX COMPOSITES

2.1. Introduction

2.2. Effect of Tool Material

2.3. Effect of Tool Geometry

2.4. Effect of Speed and Feed on Drilling

2.5. Analytical and Numerical Models to Predict Critical Thrust Force

2.6. Drilled Hole Quality on Residual Mechanical Properties

2.7. Results and Discussion

3. DRILLING OF TITANIUM ALLOY

3.1. Introduction

3.2. Effect of Tool Material

3.3. Effect of Tool Geometry

3.4. Effect of Speed and Feed on Drilling

3.5. Results and Discussion

4. DRILLING OF ALUMINIUM ALLOY

4.1. Introduction

4.2. Effect of Tool Materials

4.3. Effect of Tool Geometry

4.4. Effect of Speed and Feed on Drilling

4.5. Results and Discussion

5. DRILLING OF MULTIMATERIALS

5.1. Requirements of Cutting Tool.

5.2. Quality of Machined Holes

5.3. Results and Discussion

6. CONCLUSIONS

Chapter 11 3D MODELING OF DRILLING PROCESS OF AISI 1010 STEEL

2. MODEL DESCRIPTION

2.1. General Feature

2.2. FE Model

3. EXPERIMENTAL SETUP

3.1. Cutting Condition

3.2. Thrust Force and Torque Measurement

3.3. Temperature Measurement

4.1. Effect of Feed Rate

4.2. Effect of Cutting Speed

4.3. Effect of Friction

5. CONCLUSION

Chapter 12 PCA BASED NN APPROACH FOR DRILL WEAR PREDICTION IN DRILLING MILD STEEL SPECIMEN

2. BACK PROPAGATION NEURAL NETWORK

3. PRINCIPAL COMPONENT ANALYSIS

4. EXPERIMENTAL SET UP

4.1. Static Calibration of the Dynamometer

4.2. Dynamic Calibration of the Dynamometer

5. RESULTS AND DISCUSSION

5.1. Wear Prediction in BPNN

5.2. Wear Prediction by PCA Based NN

6. CONCLUSION

Generalized Conclusion

Conclusion Derived from Observation

Chapter 13 2D FINITE ELEMENT ANALYSIS OF SLOT MILLING

2. FINITE ELEMENT MODELLING OF SLOT MILLING

2.1. General Features

2.2. Finite Element Model

3. RESULTS OF FINITE ELEMENT ANALYSIS AND DISCUSSION

3.1. Comparison of Calculated and Measured Forces

3.2. Temperature Distribution in the Workpiece and Cutting Tool

3.3. Effect of Friction on Cutting Forces

4. CONCLUSION

Chapter 14 MODELING FRACTAL DIMENSION IN CNC MILLING OF BRASS USING ARTIFICIAL NEURAL NETWORK

2. BASICS OF FRACTAL DIMENSION

3. ARTIFICIAL NEURAL NETWORK

4. EXPERIMENTAL SCHEME

4.1. Design of Experiment

4.2. Equipment Used

4.3. Cutting Tool Used

4.4. Work Piece Material

4.5. Response Variable Selected.

4.6. Fractal Dimension Measurement

5. NEURAL NETWORK MODELING

5.1. Training of the Network

5.2. Initialization of Weights

5.3. Generalization of the Models

5.4. Selection Criterion of the Best Network

6. RESULTS AND DISCUSSION

7. CONCLUSIONS

Chapter 15 WIRE ELECTRODE WEAR IN WEDM: AN EXPERIMENTAL INVESTIGATION DURING PRODUCTION OF KEY CHAIN DIE CAVITY

2. EXPERIMENTAL PLANNING

3. EXPERIMENTAL RESULTS AND ANALYSIS FOR PARAMETRIC OPTIMIZATION

4. VALIDITY TEST

5. DEVELOPMENT OF MATHEMATICAL MODELS

5.1. Models for WEDM Performance Characteristics

5.2. Models for WEDM Parameters

5.3. Aditivity of the Developed Models for Machining Performance Characteristic

5.4. Analysis of the Developed Models for Parameters Setting

Chapter 16 OPTIMIZATION OF POWDER MIXED EDM (PMEDM) PROCESS WITH MULTIPLE PERFORMANCE CHARACTERISTICS USING TAGUCHI BASED GREY RELATIONAL ANALYSIS

2. GREY RELATIONAL ANALYSIS

2.1. Data Preprocessing

2.2. Grey Relational Coefficients and Grey Relational Grades

2.3. Confirmation Tests

3. EXPERIMENTAL DETAILS

3.1. Experimental Parameters and Design

3.2. Work Material and Electrode

3.3. Machining and Measurement

4.1. Best Experimental Run

4.2. Most Influential Parameter

4.3. Effect of Parameters on PMEDM Performance

4.4. Comparison between Initial and Optimal Conditions

5. CONCLUSIONS

Chapter 17 PARAMETRIC ANALYSIS ON ELECTROCHEMICAL MACHINING OF AL/SICP COMPOSITES

2. EXPERIMENTAL STUDY

2.1. Machining Cell

2.2. Control Panel

2.3. Electrolyte Circulation

2.4. Machining Processes

3. RESPONSE SURFACE METHODOLOGY.

4. RESULT AND DISCUSSION.

Notes:

Description based upon print version of record.

Includes bibliographical references and index.

ISBN:

1-62081-802-7