Intelligent e-monitoring of plastic injection molding machines.

• Other Authors: Lau, Hau Yu.
• Format: Others
• Language: English; Chinese
• Published: 2004
• Subjects: Injection molding of plastics; Plastics industry and trade; Machinery industry
• Online Access: http://library.cuhk.edu.hk/record=b5891849; http://repository.lib.cuhk.edu.hk/en/item/cuhk-324866

Lau Hau Yu. === Thesis (M.Phil.)--Chinese University of Hong Kong, 2004. === Includes bibliographical references (leaves 79-83). === Abstracts in English and Chinese. === Abstract --- p.i === Acknowledgements --- p.iv === Table of Contents --- p.vi === Chapter Chapter 1: --- Introduction --- p.1 === Chapter 1.1 --- Background --- p.1 === Chapter 1.2 --- Objective --- p.4 === Chapter Chapter 2: --- Literature Survey --- p.6 === Chapter 2.1 --- Plastic Injection Molding Process --- p.6 === Chapter 2.2 --- Monitoring and Diagnosis Methods --- p.10 === Chapter 2.3 --- Remote Monitoring --- p.12 === Chapter Chapter 3: --- Monitoring Methods --- p.15 === Chapter 3.1 --- Predict nozzle pressure and part weight using the Radial Basis Function Neural Network --- p.15 === Chapter 3.1.1 --- Motivation --- p.15 === Chapter 3.1.2 --- Background --- p.15 === Chapter 3.1.3 --- Hybrid RBF neural network --- p.17 === Chapter 3.1.4 --- Estimation of nozzle pressure --- p.21 === Chapter 3.1.5 --- Estimation of part weight: The two steps and one step methods --- p.22 === Chapter 3.2 --- Short shot Monitoring using Similarity --- p.25 === Chapter 3.2.1 --- Background --- p.25 === Chapter 3.2.2 --- The Dissimilarity Approach --- p.26 === Chapter 3.3 --- Parameter Resetting using Support Vector Machine (SVM) and Virtual Search Method (VSM) --- p.27 === Chapter 3.3.1 --- Background --- p.27 === Chapter 3.3.2 --- Support Vector Regression --- p.27 === Chapter 3.3.3 --- SVM Parameters Resetting using Virtual Search Method (VSM) --- p.31 === Chapter 3.4 --- Experiments and Results --- p.33 === Chapter 3.4.1 --- Introduction to Design of Experiment (DOE) --- p.33 === Chapter 3.4.2 --- Set-points selection based on Design of Experiment (DOE) --- p.34 === Chapter 3.4.3 --- Nozzle pressure estimation --- p.40 === Chapter 3.4.4 --- Part weight prediction using the One Step Method --- p.47 === Chapter 3.4.5 --- Similarity Monitoring using estimated nozzle pressure --- p.49 === Chapter 3.4.6 --- Similarity Monitoring using ram position --- p.54 === Chapter 3.4.7 --- Parameter Resetting using SVM and VSM --- p.61 === Chapter Chapter 4: --- The Remote Monitoring and Diagnosis System (RMDS) --- p.63 === Chapter 4.1 --- Introduction to the Remote Monitoring and Diagnosis System --- p.63 === Chapter 4.2 --- Starting Use of the Software --- p.65 === Chapter 4.3 --- Properties and Channel Settings --- p.66 === Chapter 4.3.1 --- Statistic Process Control (SPC) --- p.69 === Chapter 4.3.2 --- Settings --- p.71 === Chapter 4.3.3 --- Viewing the signals --- p.72 === Chapter 4.3.4 --- Short shot monitoring --- p.73 === Chapter 4.3.5 --- Data management --- p.73 === Chapter Chapter 5: --- Coeclusions and Future Works --- p.76 === References --- p.79 === Appendix A: Machine settings in the experiment --- p.84 === Appendix B: Measured part weight in the part weight prediction experiment --- p.86 === Appendix C: Measured part weight in the similarity monitoring experiment --- p.87 === Appendix D: Results of Parameters Resetting Experiment --- p.88 === Appendix E: List of figures --- p.89 === Appendix F: List of tables --- p.91