Injection Molding Process Modelling: Statistics, CAE, and AI Applications [Hardcover]

Injection Molding Process Modelling presents the application of CAE, statistics and AI in defect identification, control, and optimization of injection molding process for quality production. It showcases CAE in determining the optimal placement of injection points, designing cooling channels, and ensuring that the mold will produce parts with the desired specifications. The book illustrates the capability of the CAE tools to simulate molten plastic flow within a mold during the injection molding process.

Explaining how the use of CAE, statistical tools and AI enhances efficiency, accuracy, and collaboration, the book explores the contributions to injection molding in product design and visualization; prototyping and testing; mold design; and analysis and simulation. It emphasizes the integration of statistical tools for optimized efficiency and waste reduction, including statistical process control (SPC), Design of Experiments (DOE), Regression Analysis, Capability Indices, Interaction effects, and many more. The book also illustrates the predictive modelling of typical injection molded product defects using intelligent algorithms.

The book will interest industry professionals and engineers working in manufacturing, production, automation, and quality control.

1. Injection molding for plastic processing.? 2. Computer Aided modelling for plastic injection molding.? 3. Statistical modelling of plastic injection molding defects.? 4. Predictive Modelling of Injection Molding Defects.? 5. State-of-the art of artificial intelligence and prospectives in modelling of plastic injection molding.??

Prof. Tien-Chien Jen joined the University of Johannesburg in August 2015. He received his PhD in Mechanical and Aerospace Engineering from UCLA, specializing in thermal aspects of grinding. He has received several competitive grants for his research, including tholS!