{"product_id":"computer-modeling-for-injection-molding-isbn-9780470602997","title":"Computer Modeling for Injection Molding","description":"This book covers a wide range of applications and uses of simulation and modeling techniques in polymer injection molding, filling a noticeable gap in the literature of design, manufacturing, and the use of plastics injection molding. The authors help readers solve problems in the advanced control, simulation, monitoring, and optimization of injection molding processes. The book provides a tool for researchers and engineers to calculate the mold filling, optimization of processing control, and quality estimation before prototype molding. \u003cp\u003ePREFACE xiii\u003c\/p\u003e \u003cp\u003eCONTRIBUTORS xv\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART I BACKGROUND 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Introduction 3\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eHuamin Zhou\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction of Injection Molding, 3\u003c\/p\u003e \u003cp\u003e1.2 Factors Influencing Quality, 5\u003c\/p\u003e \u003cp\u003e1.3 Computer Modeling, 10\u003c\/p\u003e \u003cp\u003e1.4 Objective of This Book, 17\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Background 25\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eHuamin Zhou\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Molding Materials, 25\u003c\/p\u003e \u003cp\u003e2.2 Product Design, 31\u003c\/p\u003e \u003cp\u003e2.3 Mold Design, 34\u003c\/p\u003e \u003cp\u003e2.4 Molding Process, 37\u003c\/p\u003e \u003cp\u003e2.5 Process Control, 43\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART II SIMULATION 49\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Mathematical Models for the Filling and Packing Simulation 51\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eHuamin Zhou, Zixiang Hu, and Dequn Li\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Material Constitutive Relationships and Viscosity Models, 51\u003c\/p\u003e \u003cp\u003e3.2 Thermodynamic Relationships, 56\u003c\/p\u003e \u003cp\u003e3.3 Thermal Properties Model, 58\u003c\/p\u003e \u003cp\u003e3.4 Governing Equations for Fluid Flow, 59\u003c\/p\u003e \u003cp\u003e3.5 Boundary Conditions, 65\u003c\/p\u003e \u003cp\u003e3.6 Model Simplifications, 67\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Numerical Implementation for the Filling and Packing Simulation 71\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eHuamin Zhou, Zixiang Hu, Yun Zhang, and Dequn Li\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Numerical Methods, 71\u003c\/p\u003e \u003cp\u003e4.2 Tracking of Moving Melt Fronts, 101\u003c\/p\u003e \u003cp\u003e4.3 Methods for Solving Algebraic Equations, 113\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Cooling Simulation 129\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eYun Zhang and Huamin Zhou\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction, 129\u003c\/p\u003e \u003cp\u003e5.2 Modeling, 131\u003c\/p\u003e \u003cp\u003e5.3 Numerical Implementation Based on Boundary Element Method, 136\u003c\/p\u003e \u003cp\u003e5.4 Acceleration Method, 143\u003c\/p\u003e \u003cp\u003e5.5 Simulation for Transient Mold Temperature Field, 150\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Residual Stress and Warpage Simulation 157\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eFen Liu, Lin Deng, and Huamin Zhou\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Residual Stress Analysis, 157\u003c\/p\u003e \u003cp\u003e6.2 Warpage Simulation, 170\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Microstructure and Morphology Simulation 195\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eHuamin Zhou, Fen Liu, and Peng Zhao\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Types of Polymeric Systems, 195\u003c\/p\u003e \u003cp\u003e7.2 Crystallization, 196\u003c\/p\u003e \u003cp\u003e7.3 Phase Morphological Evolution in Polymer Blends, 203\u003c\/p\u003e \u003cp\u003e7.4 Orientation, 214\u003c\/p\u003e \u003cp\u003e7.5 Numerical Implementation, 220\u003c\/p\u003e \u003cp\u003e7.6 Microstructure-Property Relationships, 224\u003c\/p\u003e \u003cp\u003e7.7 Multiscale Modeling and Simulation, 228\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Development and Application of Simulation Software 237\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eZhigao Huang, Zixiang Hu, and Huamin Zhou\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Development History of Injection Molding Simulation Models, 237\u003c\/p\u003e \u003cp\u003e8.2 Development History of Injection Molding Simulation Software, 240\u003c\/p\u003e \u003cp\u003e8.3 The Process of Performing Simulation Software, 243\u003c\/p\u003e \u003cp\u003e8.4 Application of Simulation Results, 246\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART III OPTIMIZATION 255\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Noniterative Optimization Methods 257\u003c\/b\u003e\u003cbr\u003e\u003ci\u003ePeng Zhao, Yuehua Gao, Huamin Zhou, and Lih-Sheng Turng\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Taguchi Method, 258\u003c\/p\u003e \u003cp\u003e9.2 Gray Relational Analysis, 260\u003c\/p\u003e \u003cp\u003e9.3 Expert Systems, 261\u003c\/p\u003e \u003cp\u003e9.4 Case-Based Reasoning, 266\u003c\/p\u003e \u003cp\u003e9.5 Fuzzy Systems, 268\u003c\/p\u003e \u003cp\u003e9.6 Injection Molding Applications, 274\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Intelligent Optimization Algorithms 283\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eYuehua Gao, Peng Zhao, Lih-Sheng Turng, and Huamin Zhou\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Genetic Algorithms, 283\u003c\/p\u003e \u003cp\u003e10.2 Simulated Annealing Algorithms, 285\u003c\/p\u003e \u003cp\u003e10.3 Particle Swarm Algorithms, 287\u003c\/p\u003e \u003cp\u003e10.4 Ant Colony Algorithms, 289\u003c\/p\u003e \u003cp\u003e10.5 Hill Climbing Algorithms, 290\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Optimization Methods Based on Surrogate Models 293\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eYuehua Gao, Lih-Sheng Turng, Peng Zhao, and Huamin Zhou\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Response Surface Method, 294\u003c\/p\u003e \u003cp\u003e11.2 Artificial Neural Network, 296\u003c\/p\u003e \u003cp\u003e11.3 Support Vector Regression, 298\u003c\/p\u003e \u003cp\u003e11.4 Kriging Model, 301\u003c\/p\u003e \u003cp\u003e11.5 Gaussian Process, 304\u003c\/p\u003e \u003cp\u003e11.6 Injection Molding Applications of Optimization Methods Based on Surrogate Models, 305\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART IV PROCESS CONTROL 313\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Feedback Control 315\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eYi Yang and Furong Gao\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Traditional Feedback Control, 315\u003c\/p\u003e \u003cp\u003e12.2 Adaptive Control Strategy, 316\u003c\/p\u003e \u003cp\u003e12.3 Model Predictive Control Strategy, 318\u003c\/p\u003e \u003cp\u003e12.4 Optimal Control Strategy, 322\u003c\/p\u003e \u003cp\u003e12.5 Intelligent Control Strategy, 329\u003c\/p\u003e \u003cp\u003e12.6 Summary of Advanced Feedback Control, 335\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Learning Control 339\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eYi Yang and Furong Gao\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Learning Control, 339\u003c\/p\u003e \u003cp\u003e13.2 Two-Dimensional (2D) Control, 345\u003c\/p\u003e \u003cp\u003e13.3 Conclusions, 350\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Multivariate Statistical Process Control 355\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eYuan Yao and Furong Gao\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14.1 Statistical Process Control, 355\u003c\/p\u003e \u003cp\u003e14.2 Multivariate Statistical Process Control, 356\u003c\/p\u003e \u003cp\u003e14.3 MSPC for Batch Processes, 358\u003c\/p\u003e \u003cp\u003e14.4 MSPC for Injection Molding Process, 359\u003c\/p\u003e \u003cp\u003e14.5 Conclusions, 373\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Direct Quality Control 377\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eYi Yang and Furong Gao\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15.1 Review of Product Weight Control, 377\u003c\/p\u003e \u003cp\u003e15.2 Methods, 378\u003c\/p\u003e \u003cp\u003e15.3 Experimental Results and Discussion, 380\u003c\/p\u003e \u003cp\u003e15.4 Conclusions, 389\u003c\/p\u003e \u003cp\u003eReferences, 389\u003c\/p\u003e \u003cp\u003eINDEX 391\u003c\/p\u003e \u003cp\u003e“Overall, this book can be recommended for a reader interested in getting an overall idea of the contribution of computer science to injection molding, or to a researcher looking for an updated review of the latest applications of numerical techniques to this technology.”  (\u003ci\u003eMaterials Views\u003c\/i\u003e, 22 October  2013)\u003c\/p\u003e  \u003cp\u003e\u003cb\u003eHUAMIN ZHOU, PhD,\u003c\/b\u003e is Vice Dean of the School of Materials Science and Engineering and Vice Director of the State Key Laboratory of Materials Processing and Die \u0026amp; Mould Technology at the Huazhong University of Science and Technology, Wuhan, China. Dr. Zhou has published more than 200 peer-reviewed papers. His research examines polymer processing, numerical simulation, and process optimization and control.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eA guide to optimizing the manufacture of high-quality plastic products\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eInjection molding is the most popular process for manufacturing plastic products, including automotive parts, household articles, consumer electronics, and several other everyday items. Rather than relying on costly trial-and-error methods, manufacturers are increasingly turning to sophisticated computer modeling in order to optimize the design and performance of new injection molding plastic products. Moreover, computer modeling enables them to design the most efficient and cost-effective processes to manufacture these products.\u003c\/p\u003e \u003cp\u003e\u003ci\u003eComputer Modeling for Injection Molding\u003c\/i\u003e is a systematic and comprehensive book written by a team of leading experts that guide readers through the latest advances in the field. Following the authors' clear explanations, readers will discover a host of new computer modeling tools that enable them to design and manufacture high-quality injection molding products. The book is divided into four parts:\u003c\/p\u003e \u003cul\u003e \u003cli\u003ePart One: Background\u003c\/li\u003e \u003cli\u003ePart Two: Simulation\u003c\/li\u003e \u003cli\u003ePart Three: Optimization\u003c\/li\u003e \u003cli\u003ePart Four: Process Control\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eTopics include some of the latest advances in technology and computing, such as parallel computing, the acceleration method, intelligent optimization methods, and learning control for injection molding. Throughout the book, the authors set forth problems that typically arise in computer modeling alongside easy-to-implement solutions. Case studies documenting successful applications of computer modeling for injection molding offer important lessons of what to do and what not to do.\u003c\/p\u003e \u003cp\u003e\u003ci\u003eComputer Modeling for Injection Molding\u003c\/i\u003e provides students and researchers new to the field with all the basic information needed to get started. It also offers experienced plastics engineers the latest advances in the field needed to design, optimize, and manufacture high-quality plastic products as efficiently as possible.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47988969013477,"sku":"NP9780470602997","price":167.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9780470602997.jpg?v=1761782252","url":"https:\/\/k12savings.com\/es\/products\/computer-modeling-for-injection-molding-isbn-9780470602997","provider":"K12savings","version":"1.0","type":"link"}