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عدد المساهمات : 19001 التقييم : 35505 تاريخ التسجيل : 01/07/2009 الدولة : مصر العمل : مدير منتدى هندسة الإنتاج والتصميم الميكانيكى
| موضوع: كتاب Computer Modeling for Injection Molding الخميس 17 أكتوبر 2019, 11:31 pm | |
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أخوانى فى الله أحضرت لكم كتاب Computer Modeling for Injection Molding Simulation, Optimization, and Control Edited by Huamin Zhou Huazhong University of Science and Technology, Wuhan, Hubei, China
و المحتوى كما يلي :
Contents Preface Xiii Contributors Xv Part I Background 1 1 Introduction 3 Huamin Zhou 1.1 Introduction of Injection Molding, 3 1.1.1 The injection molding process, 3 1.1.2 Importance of molding quality, 3 1.2 Factors Influencing Quality, 5 1.2.1 Molding polymer, 5 1.2.2 Plastic product, 6 1.2.3 Injection mold, 7 1.2.4 Process conditions, 7 1.2.5 Injection molding machine, 8 1.2.6 Interrelationship, 9 1.3 Computer Modeling, 10 1.3.1 Review of computer applications, 11 1.3.2 Computer modeling in quality enhancement, 11 1.3.3 Numerical simulation, 13 1.3.4 Optimization, 14 1.3.5 Process control, 15 1.4 Objective of This Book, 17 References, 18 2 Background 25 Huamin Zhou 2.1 Molding Materials, 25 2.1.1 Rheology, 25 2.1.2 Thermal properties, 27 vvi CONTENTS 2.1.3 PVT behavior, 29 2.1.4 Morphology, 30 2.2 Product Design, 31 2.2.1 Wall thickness, 31 2.2.2 Draft, 32 2.2.3 Parting plane, 32 2.2.4 Sharp corners, 33 2.2.5 Undercuts, 33 2.2.6 Bosses and cored holes, 33 2.2.7 Ribs, 33 2.3 Mold Design, 34 2.3.1 Mold cavity, 34 2.3.2 Parting plane, 35 2.3.3 Runner system, 36 2.3.4 Cooling system, 37 2.4 Molding Process, 37 2.4.1 The molding cycle, 38 2.4.2 Flow in the cavity, 40 2.4.3 Orientation, 41 2.4.4 Residual stresses, shrinkage, and warpage, 41 2.5 Process Control, 43 2.5.1 Characteristics of injection molding as a batch process, 45 2.5.2 Typical control problems in injection molding, 45 References, 47 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 3.1.1 Newtonian fluids, 51 3.1.2 Generalized Newtonian fluids, 52 3.1.3 Viscoelastic fluids, 54 3.2 Thermodynamic Relationships, 56 3.2.1 Constant specific volume, 57 3.2.2 Spencer–Gilmore model, 57 3.2.3 Tait model, 57 3.3 Thermal Properties Model, 58 3.4 Governing Equations for Fluid Flow, 59 3.4.1 Mass conservation equation, 59 3.4.2 Momentum conservation equation, 60 3.4.3 Energy conservation equation, 62 3.4.4 General transport equation, 64 3.5 Boundary Conditions, 65 3.5.1 Pressure boundary conditions, 66 3.5.2 Temperature boundary conditions, 66 3.5.3 Slip boundary condition, 66 3.6 Model Simplifications, 67 3.6.1 Hele–shaw model, 67 3.6.2 Governing equations for the filling phase, 68 3.6.3 Governing equations for the packing phase, 69 References, 69CONTENTS vii 4 Numerical Implementation for the Filling and Packing Simulation 71 Huamin Zhou, Zixiang Hu, Yun Zhang, and Dequn Li 4.1 Numerical Methods, 71 4.1.1 Finite difference method, 72 4.1.2 Finite volume method, 76 4.1.3 Finite element method, 85 4.1.4 Mesh-less methods, 95 4.2 Tracking of Moving Melt Fronts, 101 4.2.1 Overview, 101 4.2.2 FAN, 104 4.2.3 VOF, 105 4.2.4 Level set methods, 110 4.3 Methods for Solving Algebraic Equations, 113 4.3.1 Overview, 113 4.3.2 Direct methods, 114 4.3.3 Iterative methods, 116 4.3.4 Parallel computing, 121 References, 125 5 Cooling Simulation 129 Yun Zhang and Huamin Zhou 5.1 Introduction, 129 5.2 Modeling, 131 5.2.1 Cycle-averaged temperature field, 131 5.2.2 Cycle-averaged boundary conditions, 132 5.2.3 Coupling calculation procedure, 134 5.2.4 Calculating cooling time, 135 5.3 Numerical Implementation Based on Boundary Element Method, 136 5.3.1 Boundary integral equation, 136 5.3.2 Numerical implementation, 138 5.4 Acceleration Method, 143 5.4.1 Analysis of the coefficient matrix, 143 5.4.2 The approximated sparsification method, 144 5.4.3 The splitting method, 145 5.4.4 The fast multipole boundary element method, 146 5.4.5 Results and discussion, 148 5.5 Simulation for Transient Mold Temperature Field, 150 References, 154 6 Residual Stress and Warpage Simulation 157 Fen Liu, Lin Deng, and Huamin Zhou 6.1 Residual Stress Analysis, 157 6.1.1 Development of residual stress, 157 6.1.2 Model prediction, 159 6.1.3 Numerical simulation, 163 6.1.4 Case study, 165 6.2 Warpage Simulation, 170 6.2.1 Development of warpage, 172 6.2.2 Model prediction, 173 6.2.3 Implementation with surface model, 182 6.2.4 Case study, 186 References, 190viii CONTENTS 7 Microstructure and Morphology Simulation 195 Huamin Zhou, Fen Liu, and Peng Zhao 7.1 Types of Polymeric Systems, 195 7.1.1 Thermoplastics and thermosets, 195 7.1.2 Amorphous and crystalline polymers, 196 7.1.3 Blends and composites, 196 7.2 Crystallization, 196 7.2.1 Fundamentals, 196 7.2.2 Modeling, 197 7.2.3 Case study, 202 7.3 Phase Morphological Evolution in Polymer Blends, 203 7.3.1 Fundamentals, 205 7.3.2 Modeling, 207 7.3.3 Case study, 213 7.4 Orientation, 214 7.4.1 Molecular orientation, 215 7.4.2 Fiber orientation, 216 7.4.3 Case study, 218 7.5 Numerical Implementation, 220 7.5.1 Coupled procedure, 220 7.5.2 Stable scheme of the FEM, 221 7.5.3 Formulations of the velocity and pressure equations, 222 7.5.4 Formulations of temperature and microstructure equations, 223 7.6 Microstructure-Property Relationships, 224 7.6.1 Effect of crystallinity on property, 224 7.6.2 Effect of phase morphology on property, 225 7.6.3 Effect of orientation on property, 226 7.7 Multiscale Modeling and Simulation, 228 7.7.1 Molecular scale methods, 229 7.7.2 Microscale methods, 229 7.7.3 Meso/macroscale methods, 230 7.7.4 Multiscale strategies, 231 References, 231 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 8.1.1 One-dimensional models, 238 8.1.2 2.5D models, 238 8.1.3 Three-dimensional models, 240 8.2 Development History of Injection Molding Simulation Software, 240 8.3 The Process of Performing Simulation Software, 243 8.3.1 Geometry modeling, 244 8.3.2 Selection of material, 245 8.3.3 Setting processing parameters, 246 8.4 Application of Simulation Results, 246 8.4.1 Dynamic display of melt flow front, 246 8.4.2 Cavity pressure, 246 8.4.3 Pressure at injection location, 247 8.4.4 Polymer temperature, 247 8.4.5 Shear rate, 247 8.4.6 Shear stress, 247CONTENTS ix 8.4.7 Weld lines, 247 8.4.8 Air traps, 248 8.4.9 Shrinkage index, 250 8.4.10 Cooling evaluation, 250 8.4.11 Warpage prediction, 251 References, 251 PART III OPTIMIZATION 255 9 Noniterative Optimization Methods 257 Peng Zhao, Yuehua Gao, Huamin Zhou, and Lih-Sheng Turng 9.1 Taguchi Method, 258 9.1.1 Orthogonal arrays, 258 9.1.2 Analysis of the S/N ratio, 259 9.1.3 Analysis of variance, 259 9.1.4 Taguchi technology, 259 9.2 Gray Relational Analysis, 260 9.2.1 Data preprocessing, 260 9.2.2 Gray relational coefficient and gray relational grade, 260 9.3 Expert Systems, 261 9.3.1 Knowledge base, 262 9.3.2 Inference engine, 263 9.4 Case-Based Reasoning, 266 9.4.1 Case representation, 266 9.4.2 Case retrieval, 267 9.4.3 Case adaptation, 267 9.5 Fuzzy Systems, 268 9.5.1 Fuzzy theory, 269 9.5.2 Fuzzy inference, 272 9.5.3 A fuzzy system for part defect correction, 274 9.6 Injection Molding Applications, 274 9.6.1 Review of noniteration optimization methods, 274 9.6.2 Application of the taguchi method, 276 9.6.3 Application of case-based reasoning and fuzzy systems, 278 References, 281 10 Intelligent Optimization Algorithms 283 Yuehua Gao, Peng Zhao, Lih-Sheng Turng, and Huamin Zhou 10.1 Genetic Algorithms, 283 10.1.1 Chromosome representation, 284 10.1.2 Selection, 284 10.1.3 Crossover and mutation operations, 284 10.1.4 Fitness function and termination, 285 10.2 Simulated Annealing Algorithms, 285 10.2.1 The fundamentals of the simulated annealing algorithm, 286 10.2.2 Optimum design algorithm for simulated annealing, 287 10.3 Particle Swarm Algorithms, 287 10.3.1 General procedures, 287 10.3.2 Determination of parameters, 288 10.4 Ant Colony Algorithms, 289 10.5 Hill Climbing Algorithms, 290x CONTENTS 10.5.1 General procedure, 290 10.5.2 Flow path generation with hill climbing algorithms, 290 References, 291 11 Optimization Methods Based on Surrogate Models 293 Yuehua Gao, Lih-Sheng Turng, Peng Zhao, and Huamin Zhou 11.1 Response Surface Method, 294 11.1.1 RSM theory, 294 11.1.2 Modeling error estimation, 295 11.1.3 Optimization process using RSM, 295 11.2 Artificial Neural Network, 296 11.2.1 Back propagation network, 296 11.2.2 BPN training process, 298 11.2.3 Optimization process based on ANN, 298 11.3 Support Vector Regression, 298 11.3.1 SVR theory, 299 11.3.2 Lagrange multipliers, 300 11.3.3 Kernel function, 300 11.3.4 Selection of SVR parameters, 301 11.4 Kriging Model, 301 11.4.1 Kriging model theory, 301 11.4.2 The correlation function, 302 11.4.3 Optimization design based on the kriging surrogate model, 302 11.5 Gaussian Process, 304 11.6 Injection Molding Applications of Optimization Methods Based on Surrogate Models, 305 11.6.1 Application of the ANN model, 305 11.6.2 Application of the SVR model, 307 11.6.3 Application of the kriging model, 309 References, 312 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 12.3.1 GPC design for barrel temperature control, 320 12.3.2 GPC controller parameter tuning, 321 12.3.3 Experimental test results, 322 12.4 Optimal Control Strategy, 322 12.4.1 TOC for barrel temperature start-up control, 323 12.4.2 Simulation results, 324 12.4.3 Experimental test results, 329 12.5 Intelligent Control Strategy, 329 12.5.1 Fuzzy injection velocity controller, 330 12.5.2 Fuzzy feed forward controller, 333 12.5.3 Test with different conditions, 333 12.6 Summary of Advanced Feedback Control, 335 References, 337CONTENTS xi 13 Learning Control 339 Yi Yang and Furong Gao 13.1 Learning Control, 339 13.1.1 Learning control for injection velocity profiling, 340 13.2 Two-Dimensional (2D) Control, 345 13.2.1 2D control of packing pressure, 346 13.3 Conclusions, 350 References, 352 14 Multivariate Statistical Process Control 355 Yuan Yao and Furong Gao 14.1 Statistical Process Control, 355 14.2 Multivariate Statistical Process Control, 356 14.2.1 Principal component analysis, 356 14.2.2 PCA-based process monitoring and fault diagnosis, 357 14.2.3 Normalization, 358 14.3 MSPC for Batch Processes, 358 14.4 MSPC for Injection Molding Process, 359 14.4.1 Phase-based sub-PCA, 360 14.4.2 Sub-PCA for batch processes with uneven operation durations, 361 14.4.3 Sub-PCA with limited reference data, 363 14.4.4 Applications, 365 14.5 Conclusions, 373 References, 373 15 Direct Quality Control 377 Yi Yang and Furong Gao 15.1 Review of Product Weight Control, 377 15.2 Methods, 378 15.2.1 Weight prediction using PCR model, 378 15.2.2 Overall weight control scheme and feedback adjustment, 379 15.3 Experimental Results and Discussion, 380 15.3.1 Factor screening experiment, 380 15.3.2 PCR modeling of product weight, 382 15.3.3 Closed-loop weight control based on PCR model, 387 15.4 Conclusions, 389 References, 389 INDEX
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