Computer Modeling for Injection Molding: Simulation, Optimization, and Control

A guide to optimizing the manufacture of high–quality plastic products Injection 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. Computer Modeling for Injection Molding 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: Part One: Background Part Two: Simulation Part Three: Optimization Part Four: Process Control Topics 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. Computer Modeling for Injection Molding 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.

PREFACE xiii CONTRIBUTORS xv PART I BACKGROUND 1 1 Introduction 3 Huamin Zhou 1.1 Introduction of Injection Molding, 3 1.2 Factors Influencing Quality, 5 1.3 Computer Modeling, 10 1.4 Objective of This Book, 17 2 Background 25 Huamin Zhou 2.1 Molding Materials, 25 2.2 Product Design, 31 2.3 Mold Design, 34 2.4 Molding Process, 37 2.5 Process Control, 43 PART II SIMULATION 49 3 Mathematical Models for the Filling and Packing Simulation 51 Huamin Zhou, Zixiang Hu, and Dequn Li 3.1 Material Constitutive Relationships and Viscosity Models, 51 3.2 Thermodynamic Relationships, 56 3.3 Thermal Properties Model, 58 3.4 Governing Equations for Fluid Flow, 59 3.5 Boundary Conditions, 65 3.6 Model Simplifications, 67 4 Numerical Implementation for the Filling and Packing Simulation 71 Huamin Zhou, Zixiang Hu, Yun Zhang, and Dequn Li 4.1 Numerical Methods, 71 4.2 Tracking of Moving Melt Fronts, 101 4.3 Methods for Solving Algebraic Equations, 113 5 Cooling Simulation 129 Yun Zhang and Huamin Zhou 5.1 Introduction, 129 5.2 Modeling, 131 5.3 Numerical Implementation Based on Boundary Element Method, 136 5.4 Acceleration Method, 143 5.5 Simulation for Transient Mold Temperature Field, 150 6 Residual Stress and Warpage Simulation 157 Fen Liu, Lin Deng, and Huamin Zhou 6.1 Residual Stress Analysis, 157 6.2 Warpage Simulation, 170 7 Microstructure and Morphology Simulation 195 Huamin Zhou, Fen Liu, and Peng Zhao 7.1 Types of Polymeric Systems, 195 7.2 Crystallization, 196 7.3 Phase Morphological Evolution in Polymer Blends, 203 7.4 Orientation, 214 7.5 Numerical Implementation, 220 7.6 Microstructure–Property Relationships, 224 7.7 Multiscale Modeling and Simulation, 228 8 Development and Application of Simulation Software 237 Zhigao Huang, Zixiang Hu, and Huamin Zhou 8.1 Development History of Injection Molding Simulation Models, 237 8.2 Development History of Injection Molding Simulation Software, 240 8.3 The Process of Performing Simulation Software, 243 8.4 Application of Simulation Results, 246 PART III OPTIMIZATION 255 9 Noniterative Optimization Methods 257 Peng Zhao, Yuehua Gao, Huamin Zhou, and Lih–Sheng Turng 9.1 Taguchi Method, 258 9.2 Gray Relational Analysis, 260 9.3 Expert Systems, 261 9.4 Case–Based Reasoning, 266 9.5 Fuzzy Systems, 268 9.6 Injection Molding Applications, 274 10 Intelligent Optimization Algorithms 283 Yuehua Gao, Peng Zhao, Lih–Sheng Turng, and Huamin Zhou 10.1 Genetic Algorithms, 283 10.2 Simulated Annealing Algorithms, 285 10.3 Particle Swarm Algorithms, 287 10.4 Ant Colony Algorithms, 289 10.5 Hill Climbing Algorithms, 290 11 Optimization Methods Based on Surrogate Models 293 Yuehua Gao, Lih–Sheng Turng, Peng Zhao, and Huamin Zhou 11.1 Response Surface Method, 294 11.2 Artificial Neural Network, 296 11.3 Support Vector Regression, 298 11.4 Kriging Model, 301 11.5 Gaussian Process, 304 11.6 Injection Molding Applications of Optimization Methods Based on Surrogate Models, 305 PART IV PROCESS CONTROL 313 12 Feedback Control 315 Yi Yang and Furong Gao 12.1 Traditional Feedback Control, 315 12.2 Adaptive Control Strategy, 316 12.3 Model Predictive Control Strategy, 318 12.4 Optimal Control Strategy, 322 12.5 Intelligent Control Strategy, 329 12.6 Summary of Advanced Feedback Control, 335 13 Learning Control 339 Yi Yang and Furong Gao 13.1 Learning Control, 339 13.2 Two–Dimensional (2D) Control, 345 13.3 Conclusions, 350 14 Multivariate Statistical Process Control 355 Yuan Yao and Furong Gao 14.1 Statistical Process Control, 355 14.2 Multivariate Statistical Process Control, 356 14.3 MSPC for Batch Processes, 358 14.4 MSPC for Injection Molding Process, 359 14.5 Conclusions, 373 15 Direct Quality Control 377 Yi Yang and Furong Gao 15.1 Review of Product Weight Control, 377 15.2 Methods, 378 15.3 Experimental Results and Discussion, 380 15.4 Conclusions, 389 References, 389 INDEX 391

HUAMIN ZHOU, PhD, is Vice Dean of the School of Materials Science and Engineering and Vice Director of the State Key Laboratory of Materials Processing and Die & 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.