TY - BOOK
T1 - Injection Molding Process Modelling
T2 - Statistics, CAE, and AI Applications
AU - Jen, Tien Chien
AU - Mharakurwa, Edwell Tafara
AU - Otieno, Steven Otieno
AU - Mwema, Fredrick Madaraka
AU - Wambua, Job Maveke
PY - 2024/9/10
Y1 - 2024/9/10
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85204542952&partnerID=8YFLogxK
U2 - 10.1201/9781003492498
DO - 10.1201/9781003492498
M3 - Book
AN - SCOPUS:85204542952
SN - 9781032795201
BT - Injection Molding Process Modelling
PB - CRC Press
CY - Boca Raton, United States
ER -