Injection Molding Process Control, Monitoring, and Optimization

Chapter 1 INJECTION MOLDING: MACHINE AND PROCESS 1.1 Introduction of general polymer processing 1.2 Polymer material and characteristics 1.3 Injection molding machine 1.4 Injection molding process Chapter 2 EVOLUTION OF SYSTEMS TECHNOLOGIES IN INJECTION MOLDING 2.1 Introduction of systems technology 2.2 Evolution of process control technology in injection molding 2.3 Evolution of process monitoring technology in injection molding 2.4 Evolution of process optimization technology in injection molding Control Chapter 3 FEEDBACK CONTROL ALGORITHMS DEVELOPED FOR CONTINUOUS PROCESSES 3.1 Introduction of feedback control background 3.2 Traditional feedback control: PID 3.3 Adaptive control 3.4 Model predictive control: GPC 3.5 Optimal control 3.6 Fuzzy and Artificial Neural Networks control Chapter 4 LEARNING TYPE CONTROL DEVELOPED FOR REPETITIVE PROCESS 4.1 Introduction of learning type control background 4.2 Basic iterative learning control 4.3 Optimal iterative learning control Chapter 5 TWO-DIMENSIONAL CONTROL ALGORITHMS 5.1 Introduction of two-dimensional control background 5.2 Two-dimensional robust control 5.3 Two-dimensional optimal control 5.4 Two-dimensional model predictive control Chapter 6 FAULT-TOLERANT CONTROL IN INJECTION MOLDING 6.1 Introduction of fault-tolerant control injection molding 6.2 Active fault-tolerant control with sensor failure: an example Monitoring Chapter 7 STATISTICAL PROCESS MONITORING (SPM) 7.1 Process monitoring for continuous processes 7.2 Process monitoring for batch processes Chapter 8 SPM BASED ON PHASE RECOGNITION AND HARD PARTITION STRATEGY 8.1 Data-driven phase recognition and phase partition 8.2 Phase-based SPM in injection molding 8.3 SPM with limited modeling data 8.4 Quality-oriented process monitoring Chapter 9 SPM BASED ON SOFT PHASE PARTITION STRATEGY 9.1 Transition-based soft phase partition 9.2 Soft phase-based SPM in injection molding 9.3 Dissimilarity analysis based process monitoring 9.4 Dissimilarity analysis based nonlinear process monitoring 9.5 Adaptive process monitoring in injection molding Chapter 10 TWO-DIMENSIONAL MODEL-BASED PROCESS MONITORING & FAULT DIAGNOSIS 10.1 Two dimensional dynamic principal component analysis (2D-DPCA) 10.2 2D-DPCA based process monitoring 10.3 2D-DPCA based fault diagnosis Optimization Chapter 11 IN-MOLD CAPACITIVE TRANSDUCER FOR INJECTION MOLDING PROCESS 11.1 Principle of capacitive transducers 11.2 Hardware design of the in-mold capacitive transducer 11.3 Detection of the melt flow in filling stage 11.4 Detection of in-mold status in packing & cooling stage 11.5 Application for online part weight prediction and fault detection Chapter 12 OPTIMAL PROFILING FOR FILLING STAGE 12.1 Introduction 12.2 Constant melt-front-velocity strategy 12.3 Soft-sensor development of average-flow-length 12.4 Uniform filling based on optimization 12.5 Optimal profile of injection velocity for different mold shapes Chapter 13 OPTIMAL PROFILING FOR PACKING STAGE 13.1 Introduction 13.2 Online auto-detection of gate freezing-off point 13.3 Influence of packing profile on part quality 13.4 Profiling of packing pressure Chapter 14 PARAMETER SETTING FOR PLASTICATION STAGE 14.1 Introduction 14.2 Neural network modeling of melt temperature 14.3 Optimal parameter setting Chapter 15 MODEL FREE OPTIMIZATION FOR PART QUALITY CONTROL 15.1 Model free optimization strategy for injection molding process 15.2 Gradient-based algorithm 15.3 Non-gradient-based algorithm 15.4 Part weight control via MFO 15.5 Focal length control via MFO