Study on injection molding parameters for thin-shell plastic parts using a neural network-based approach

Polymer - Plastics Technology and Engineering

Volumn 49, Issue 1, 2010, Pages 53-61

  Lin, Jen Chang ^a   Yang, Yung Kuang ^a   Hsiao, Yun Hsiang ^a   Jeng, Ming Chang ^b  

^a MINGHSIN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

^b NATIONAL CENTRAL UNIVERSITY   (Taiwan)

Author keywords

Genetic algorithm; Neural network; Optimization; Simulated annealing; Tensile strength; Warpage

Indexed keywords

BACK-PROPAGATION NEURAL NETWORKS; EFFECTIVE TOOL; HYBRID METHOD; INJECTION-MOLDING PARAMETERS; MOLDING CONDITIONS; MOLDING PROCESS; NEURAL NETWORK OPTIMIZATION; OPTIMAL PARAMETER SETTINGS; OPTIMAL SETTING; PLASTIC COMPONENTS; SIMULATED ANNEALING ALGORITHMS; WARPAGES;

ANNEALING; GENETIC ALGORITHMS; INJECTION MOLDING; NEURAL NETWORKS; PLASTIC MOLDS; PLASTIC PARTS; TENSILE STRENGTH;

SIMULATED ANNEALING;

ANNEALING; INJECTION MOLDING; NEURAL NETWORK; OPTIMIZATION; PLASTIC; TENSILE PROPERTY;

EID: 72549101386     PISSN: 03602559     EISSN: 15256111     Source Type: Journal    
DOI: 10.1080/03602550903283067     Document Type: Article

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