Title page
Copyright page
Table of Contents
Foreword
1 Injection Molding: Background
1.1 Plastic Materials and Properties
1.1.1 Plastics Classification
1.1.2 Structural Characteristics of Plastic
1.1.3 Basic Rheology Terminology
1.1.4 Non-Newtonian Flow: Phenomenon and Constitutive Equations
1.2 Plastics Processing Technologies
1.2.1 Extrusion
1.2.2 Blow Molding
1.2.3 Injection Molding Machine, Process, and Key Variables
2 Feedback Control Algorithms Developed for Continuous Processes
2.1 Introduction of Feedback Control Background
2.2 Traditional Feedback Control: PID
2.3 Adaptive Control
2.3.1 Model Estimation
2.3.2 Pole-Placement Controller Design
2.3.3 Solving the Diophantine Equation
2.3.4 Injection Velocity Adaptive Control Result
2.4 Model Predictive Control
2.4.1 Basic Principle of MPC and GPC
2.4.2 Model Order Determination
2.4.3 Comparison with Pole-Placement Control
2.4.4 GPC Control with Different Conditions
2.5 Fuzzy Systems in Injection Molding Control
2.5.1 Fuzzy Inference System Background
2.5.2 Fuzzy V/P Switch-Over
2.5.3 Fuzzy V/P System Experimental Test
2.5.4 Further Improvement
3 Learning Type Control for the Injection Molding Process
3.1 Learning Type Control Background
3.2 Basic Iterative Learning Control
3.2.1 PID-Type ILC
3.2.2 Time-Delay Consideration
3.2.3 P-Type ILC for Injection Velocity
3.2.4 P-Type ILC for Packing Pressure
3.3 Optimal Iterative Learning Control
3.3.1 Problem Formulation
3.3.2 Optimal Iterative Learning Controller
3.3.3 Robust and Convergence Analysis
3.3.4 Selection of the Weighting Matrices
3.3.5 Simulation Results
3.3.6 Experimental Results of Optimal ILC
4 Two-Dimensional Control Algorithms
4.1 Two-Dimensional Control Background
4.2 Two-Dimensional Generalized Predictive Iterative Learning Control
4.2.1 2D-GPILC Control Algorithm
4.2.2 Injection Velocity Control with 2D-GPILC
4.3 Two-Dimensional Dynamic Matrix Control
4.3.1 Problem Formulation
4.3.2 Controller Design
4.3.3 Simulation Illustration
4.3.4 Experimental Test of 2D-DMC
5 Statistical Process Monitoring (SPM) of Injection Molding: Basics
5.1 Process Monitoring
5.2 Statistical Process Monitoring (SPM)
5.2.1 Data Collection and Preprocessing
5.2.2 Construction of Nominal Statistical Model
5.2.3 Application of Statistical Models
5.3 Multivariate Statistical Analysis Methods for SPM
5.3.1 Principal Component Analysis and Partial Least Squares
5.3.2 PCA/PLS-Based Statistical Process Monitoring
5.3.3 Multiway PCA/PLS
5.3.4 Multiway PCA/PLS-Based Batch Process Monitoring
5.4 Challenges in Monitoring Injection Molding Process
5.4.1 Multiple Operation Phases
5.4.2 Within-Batch and Batch-to-Batch Dynamics
5.4.3 Unequal Batch Length
6 Phase-Based SPM Strategies
6.1 Introduction
6.2 Phase-Division-Based Sub-PCA Modeling and Monitoring
6.2.1 Overview
6.2.2 Data Normalization
6.2.3 Phase Recognition and Division
6.2.4 Phase PCA Modeling
6.2.5 Statistics and Control Limits
6.2.6 Online Process Monitoring
6.2.7 Summary
6.3 Application of Phase-Based SPM to Injection Molding
6.3.1 Experimental Setup
6.3.2 Result Analysis of Phase Division and Modeling
6.3.3 Result Analysis of Process Monitoring and Fault Diagnosis
6.4 Improved Phase-Based SPM for Unequal-Length Batch Processes
6.4.1 Overview
6.4.2 Data Normalization
6.4.3 Phase Recognition and Division
6.4.4 Sub-PCA Modeling Procedure
6.4.5 Process Monitoring Procedure
6.4.6 Summary
6.5 Application of Improved Phase-Based SPM to Injection Molding
6.5.1 Experimental Setup
6.5.2 Result Analysis of Phase Division and Modeling
6.5.3 Result Analysis of Process Monitoring and Fault Diagnosis
7 Phase-Based Quality Improvement Strategies
7.1 Introduction
7.2 Phase-Based Process Analysis and End-Product Quality Prediction (Method A)
7.2.1 Phase-Based PLS Modeling
7.2.2 Phase-Based Quality-Related Process Analysis
7.2.3 Online Quality Prediction
7.3 Application of Phase PLS Model (Method A) to Injection Molding
7.3.1 Experimental Setup
7.3.2 Illustration of Phase-Based Process Analysis
7.3.3 Illustration of Phase-Based Quality Prediction
7.4 Phase-Based Process Analysis and End-Product Quality Prediction (Method B)
7.4.1 Critical Phase Identification
7.4.2 Key Variable Selection Based on Variable-Wise Unfolding
7.4.3 Phase-Based PLS Modeling Algorithm
7.4.4 Online Quality Prediction
7.5 Application of Phase PLS Model (Method B) to Injection Molding
7.5.1 Illustration of Correlation Analysis
7.5.2 Results of Quality Prediction
8 In-Mold Capacitive Transducer for Injection Molding Process
8.1 Fundamentals of Capacitive Transducers
8.2 Dielectric Properties of Polymers
8.3 Principle and Preliminary Tests of Capacitive Transducer in Injection Mold
8.4 Design of In-Mold Capacitive Transducer
8.4.1 Mold Base Design
8.4.2 Mold Insert Design
8.4.3 Capacitance Measurement
8.5 Applications in Melt Flow Detection during Filling Stage
8.5.1 Detection of Filling Start
8.5.2 Detection of V/P Transfer
8.5.3 Detection of melt flow during filling
8.6 Applications for the Packing and Cooling Stages
8.6.1 Guide to Packing Pressure Setting
8.6.2 Detection of Gate Freezing-Off Time
8.6.3 Solidification Rate Monitoring
8.7 Online Part Weight Prediction Using the Capacitive Transducer
9 Profile Setting of Injection Velocity
9.1 Constant Melt-Front-Velocity Strategy
9.2 Scheme Based on Average-flow-length
9.3 Neural Network Model of Average-flow-length
9.3.1 Inputs and Output of the Neural Network Model
9.3.2 Architecture of the Neural Network Model
9.3.3 Training Algorithm
9.3.4 Data Collection of Training and Validation Samples
9.3.5 Model Performance
9.4 Profiling Strategy via Optimization
9.5 Parabolic Velocity Profile
9.6 Piece-Wise Ramp Velocity Profile
9.7 Conclusions
10 Profile Setting of Packing Pressure
10.1 Online Autodetection of Gate Freezing-Off Point
10.1.1 Gate Freezing-Off Detection
10.1.2 Development of Autodetection System
10.1.3 Tests of Constant Packing Pressure Cases
10.1.4 Tests of Varying Packing Pressure Profile Cases
10.2 Influence of Packing Profile on Part Quality
10.2.1 Constant Packing Profile
10.2.2 Ramp Packing Profile
10.2.3 Step-Change Packing Profile
10.2.4 Summary
10.3 Profiling of Packing Pressure
10.3.1 Profiling Rules
10.3.2 Online Profiling of Constant Packing Pressure
10.3.3 Ramp Profile for Specific Thickness Distribution
10.4 Conclusions
11 Parameter Setting for the Plastication Stage
11.1 Visual Barrel System Development
11.2 Plastication Behavior
11.2.1 Melting Behavior
11.2.2 Processing Condition Effects
11.3 Neural Network Modeling of Melt Temperature
11.4 Optimal Parameter Setting for the Plastication Stage
Yi Yang
Xi Chen
Ningyun Lu
Furong Gao
Injection Molding Process
Control, Monitoring,
and Optimization
1st Edition
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| Foreword |
The polymer and plastics industries have had a profound techno-economic impact on society for almost a century. In fact, it has been suggested that the advent and use of polymers and plastics products have represented a revolutionary technological change. They are used in packaging, furniture, construction materials, automotive, aerospace, sporting goods, biomedical, electronics, communications, and so on. More importantly, they have adapted to the ever changing social and technological demands. Thus, many of the current popular products, such as smart phones, computers, and other technological innovations would be difficult to contemplate in the absence of polymers. It does not seem likely that the foreseeable future will see a reduction in the important role that polymers and plastics will play in future technological development.
Cognizant of the role that polymers played and will continue to play in our lives, a group of polymer scientists and engineers from various countries around the world founded the Polymer Processing Society (PPS) in March 1985 at the University of Akron, Akron, Ohio, USA. According to its constitution, the goal of the PPS is to foster scientific understanding and technical innovation in polymer processing by providing a discussion forum in the field for the worldwide community of engineers and scientists. Thus, PPS has attempted to achieve this goal using the following mechanisms:
Organization of annual and regional conferences rotating among the various regions of the world and the dissemination of technical content of the conferences in the form of proceedings.
The publication of the International Polymer Processing (IPP) Journal.
The publication of the Progress in Polymer Processing (PPP) Series.
So far, these activities have allowed the PPS and its members to exchange information and ideas about the evolution of the principles and methods of polymer science and engineering and their application to the generation of innovative products, processes and applications.
Since the formation of PPS, eleven PPP volumes have been published. Four distinguished leaders in the polymer processing field have served as series editors: Leszek Utracki, Warren Baker, Kun Sup Hyun, and James L. White. Two years ago, in Nuremberg-Germany, I was asked by the Executive of PPS to serve as PPP series editor. At the time, I indicated that with the help of the Advisory Editorial Board, our colleagues in the polymer processing field, and Hanser Publications, we would aim to publish at the rate of about one book every year. So far, we are meeting this goal. Already, we have two books under preparation for publication during the next two years, in addition to discussion with other potential authors/editors for subsequent years. Of course, we would be happy to produce more than one excellent book per year, if the opportunity arises. I encourage prospective authors to contact me or any of the Advisory Board members with their ideas and suggestions.
Injection molding is the most versatile, flexible, and dynamic plastics production operation. It has been used to manufacture products from practically all thermoplastic polymers, blends, composites, and nanocomposites. The versatile injection molding process can be used to manufacture, repetitively at high rates, products with complex shapes, micro to large sizes, multilayers and colors, with or without inserts. The injection molded products must satisfy a multitude of specifications relating to shape, dimensions, dimensional and shape stability, strength, surface characteristics, and other specifications associated with functionality and the requirements of the intended application. The large number of products, molders, and machinery manufacturers has led to varying types and sizes of machines and to the development of various optimum strategies for manufacturing products meeting the required specifications.
A critical aspect for the success of the injection molding process depends on understanding and control of the various steps of the injection molding process, the thermo-mechanical history experienced by the polymer throughout the process, and the impact of this history on the characteristics of the final product. As many of these interactions and concepts are complex, it is very important to develop a monitoring strategy that permits the identification of the status and responses of the critical process variables. Overall, a successful injection molding process must be coupled to a successful process monitoring, optimization, and control strategy.
In view of the above, it is a pleasure to introduce this year the important book entitled Injection Molding Process Control, Monitoring, and Optimization. I am confident that the book will represent a major contribution to the science and practice of injection molding. It should satisfy some of the critical needs of injection molding machine manufacturers, mold and product designers, and molders. Moreover, the book should be helpful to researchers and teachers in the fields of injection molding and process control.
Finally, on behalf of the Polymer Processing Society and the PPP Editorial Advisory Board, I would like to express our sincerest thanks and appreciation to the authors for the intensive effort they made to prepare this valuable and important book. We owe a lot of thanks to Dr. Mark Smith and Ms. Cheryl Hamilton and other Hanser staff for their efforts to ensure a timely completion of this project and for the organization of the copyediting and production of the book.
Musa R. Kamal
Series Editor
| 1 | Injection Molding: Background |