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LEADER 00000cam a2200505Ii 4500 
003    OCoLC 
005    20190319055257.7 
006    m     o  d         
007    cr nn|008mamaa 
008    161027s2017    si      ob    000 0 eng d 
019    SpringerEBAocn962018524 
020    9789811022517|q(electronic bk.) 
020    9811022518|q(electronic bk.) 
020    |z9789811022500 
020    |z981102250X 
024 7  10.1007/978-981-10-2251-7|2doi 
040    AZU|beng|epn|cAZU|dN$T|dGW5XE|dOSU|dOCLCO|dN$T|dOCLCQ|dCOO
       |dYDX|dIDEBK|dUAB|dUPM|dOCLCF|dIOG|dVT2|dUWO|dESU|dJBG
       |dIAD|dICW|dICN|dOTZ|dOCLCQ|dU3W|dCAUOI|dOCL|dKSU|dEZ9|dAU
       @|dOCLCQ|dWYU 
049    MAIN 
050  4 TS250 
082 04 671.823|223 
245 00 AI applications in sheet metal forming /|cShailendra Kumar,
       Hussein M.A. Hussein, editors. 
264  1 Singapore :|bSpringer,|c2017. 
300    1 online resource. 
336    text|btxt|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
347    text file|bPDF|2rda 
490 1  Topics in mining, metallurgy and materials engineering,
       |x2364-3293 
504    Includes bibliographical references. 
505 0  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. 
520    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 
       working in sheet metal industries, and will serve to 
       provide future direction to young researchers and students
       working in the area. 
650  0 Sheet-metal work|xAutomation. 
650  0 Computer integrated manufacturing systems. 
655  4 Electronic books. 
700 1  Kumar, Shailendra,|eeditor. 
700 1  Hussein, Hussein M. A.,|eeditor. 
710 2  SpringerLink|eissuing body. 
776 08 |iPrinted edition:|z9789811022500 
830  0 Topics in mining, metallurgy and materials engineering. 
830  0 Springer Engineering eBooks 2017 English+International 
856 40 |uhttps://ezp.lib.unimelb.edu.au/login?url=http://
       link.springer.com/10.1007/978-981-10-2251-7|zConnect to 
       ebook (University of Melbourne only) 
990    Springer EBA e-book collections for 2017-2019 
990    Springer Engineering 2017 
990    Batch Ebook load (bud2) - do not edit, delete or attach 
       any records. 
991    |zNEW New collection springerlink.ebooksengine2017 2019-03
       -18 
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