Table of Contents

Table of Contents

Preface pp. i-vii
Research and review studies

Chapter 1. Application of neural networks and fuzzy sets to machining and metal forming
(U. S. Dixit, Department of Mechanical Engineering, Indian Institute of Technology Guwahati, INDIA)pp. 1-30

Chapter 2. Multi-objective optimization of multi-pass milling process parameters using artificial bee colony
(R. Venkata Rao, S.V. National Institute of Technology, Gujarat,INDIA; P. J. Pawar,K.K. Wagh Institute of Engineering Education and Research, Nashik, Maharashtra, INDIA)pp. 31-50

Chapter 3. Optimization of abrasive flow machining process parameters using particle swarm optimization and simulated annealing algorithms
(P. J. Pawar, R. Venkata Rao, J. Paulo Davim)pp. 51-64

Chapter 4. Study of effects of process parameters on burr height in drilling of AISI 316 stainless steel using artificial neural network model
(V. N. Gaitonde and S.R. Karnik, B.V.B. College of Engineering & Technology, Hubli– INDIA; J. Paulo Davim)pp. 65-78

Chapter 5. Artificial neural network modelling of surface quality characteristics in abrasive water jet machining of trip steel sheet
(N. M. Vaxevanidis and A. Markopoulos, School of Pedagogical & Technological Education (ASPETE), Athens, GREECE; Te G. Petropoulos,
University of Thessaly, Volos, GREECE)pp. 79-100

Chapter 6. Multi-objective optimisation of cutting parameters for drilling aluminium
(Ramón Quiza, University of Matanzas, Matanzas, CUBA; J. Paulo Davim)pp. 101-110

Chapter 7. Application of fuzzy logic in manufacturing: a study on modelling of cutting force in turning GFRP composites
K. Palanikumar, J. Paulo Davim pp. 111-128

Chapter 8. Flank wear detection with AE signal and FNN during turning of Al/15vol%SiC-MMC
(Alakesh Manna, Punjab Engineering College, Deemed University,
Chandigarh, INDIA)pp. 129-140

Chapter 9. Integration of product development process using STEP and PDM
(S. Q. Xie, W. L. Chen, University of Auckland, Auckland, NEW ZEALAND)pp. 141-174

Index pp. 175-182