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

  • ID: 2170975
  • February 2013
  • 416 Pages
  • John Wiley and Sons Ltd
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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

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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

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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.   (Materials Views, 22 October  2013)

Note: Product cover images may vary from those shown
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