AI Applications in Sheet Metal Forming

This book comprises chapters on research work done around the globe in the area of artificial intelligence (AI) applications in sheet metal forming. The first chapter offers an introduction to various AI techniques and sheet metal forming, while subsequent chapters describe traditional procedures/methods used in various sheet metal forming processes, and focus on the automation of those processes by means of AI techniques, such as KBS, ANN, GA, CBR, etc. Feature recognition and the manufacturability assessment of sheet metal parts, process planning, strip-layout design, selecting the type and size of die components, die modeling, and predicting die life are some of the most important aspects of sheet metal work. Traditionally, these activities are highly experience-based, tedious and time consuming. In response, researchers in several countries have applied various AI techniques to automate these activities, which are covered in this book. This book will be useful for engineers workingin sheet metal industries, and will serve to provide future direction to young researchers and students working in the area.

Demonstrates applications of various AI techniques in sheet metal forming, using real industrial sheet metal parts Includes flow charts explaining the execution of the systems developed using AI techniques Presents research work that, if implemented in the sheet metal industry, could dramatically reduce the time and cost of manufacturing sheet metal parts Includes supplementary material: sn.pub/extras

Auteur
Dr. Shailendra Kumar is an Associate Professor in the Mechanical Engineering Department at S.V. National Institute of Technology, Surat, India. He received his Bachelor's degree in Production Engineering from the Regional Institute of Technology (presently National Institute of Technology), Jamshedpur, India in 1999 and his PhD from the Faculty of Engineering & Technology, Maharshi Dayanand University, Rohtak, India in 2007. His main research interests are in the area of press tool design, AI applications in manufacturing, KBS/expert systems for die design, sheet metal forming, CAPP, CAD/CAM and non-traditional manufacturing. He has successfully completed one research project for the Department of Science and Technology, Government of India and engaged in three more research projects sanctioned by national and international agencies. Three PhD scholars and 22 M. Tech. students have completed their research work under his supervision. Dr. Kumar has more than 120 research papersin reputed journals and conferences to his credit. He serves as a reviewer for many reputed journals and is a life member of the Indian Society of Mechanical Engineers (ISME), International Association of Engineers (IAENG), and World Academy of Science, Engineering & Technology (WASET), and Senior member of Universal Association of Mechanical and Aeronautical Engineers (UAMAE), The IRED, New York, USA Dr. H.M.A. Hussein is currently serving at the Faculty of Engineering, Mechanical Engineering Department, Helwan University, Cairo, Egypt. He received his PhD in Mechanical (Production) Engineering from Helwan University, Egypt in 2008. He has also served in the tool design department of many companies. His research interests include computer aided sheet metal die design, AI applications to sheet metal forming, CAD/CAM, AutoCAD application and customization, and CAPP. He has completed many research projects in the area of design and manufacturing sanctioned by various funding agencies. He is a member of the Egyptian Syndicate of Professional Engineers, and of the Egyptian Mechanical Engineers Associations.

Contenu
An overview of applications of artificial intelligence (AI) in sheet metal work.- Generic classification and representation of shape features in sheet-metal parts.- Feature Extraction and Manufacturability Assessment of Sheet Metal Parts.- Knowledge Based System for Design of Blanking Dies.- Knowledge-Based System for Design of Deep Drawing Die for Axisymmetric Parts.- An Integrated Approach for Optimized Process Planning of Multistage Deep Drawing.- Knowledge Based System for Design of Deep Drawing Die for Elliptical Shape Parts.- An Expert System for Automatic Design of Compound Dies.- Prediction of Die Life of Compound Die using ANN.- Knowledge Based System for Automatic Design of Bending Dies.