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http://ciatec.repositorioinstitucional.mx/jspui/handle/1019/161| Optimization of tensile strength in injection molded polyamide-6 pieces using neuronal network techniques and non-linear programming | |
| ROBERTO ZITZUMBO GUZMAN | |
| Acceso Abierto | |
| Atribución-NoComercial | |
| Polímeros Poliamida | |
| The main objective of this research is the optimization of tensile stress of injection molded parts of polyamide-6 to establish process conditions that maximize tensile strength of parts in a real industrial process. The methodology consisted in development of assays based on I-optimal experimental design to get a data base. Four parameters were considered as inputs: injection holding pressure, injection packing time, % wt virgin material and % wt recycled material. Measurement of maximum tensile stress in parts was made according to ISO 527-1 standard. Three models were developed by the techniques Response Surface Methodology, Back Propagation Neural Network and Generalized Regression Neural Network to predict parts maximum tensile stress. Finally, the best model (with lowest forecasting error) was optimized by Trust Region Method Based on Interior Point Techniques for Nonlinear Programming to maximize tensile strength. This proposed methodology is capable for modeling the process with low error and for stablish process conditions to obtain the maximum tensile stress on molded parts. Keywords: Plastic Injection Molding; Tensile stress; Polyamid-6; Response Surface; Backpropagation Neural Network; Generalized Regression Neural Network; Nonlinear programming. | |
| 2018 | |
| Artículo | |
| Inglés | |
| Empresas Estudiantes Investigadores Maestros | |
| PLÁSTICOS | |
| Versión publicada | |
| publishedVersion - Versión publicada | |
| Aparece en las colecciones: | Artículos de investigación |
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| Fichero | Tamaño | Formato | |
|---|---|---|---|
| Optimitation.pdf | 1.17 MB | Adobe PDF | Visualizar/Abrir |