Prediction of Optimum Parameters for Injection Molding Machines
| Autor: | Yang Ching-Cheng, 楊景程 |
|---|---|
| Rok vydání: | 2001 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 89 In the injection molding process, appropriate machining parameters are vital to expected productivity and quality. In general, only experienced and skilled operators are capable of choosing the machining parameters. Although manufacturers of injection molding machines usually provide users with a set of machining-parameter tables, it doesn’t always serve the needs of users, because the tables are based on hundreds of costly experiments under specific conditions. This paper presents an effective and efficient procedure to determine optimum machining-parameters. We use Taguchi quality design method incorporated with analysis of variance to figure out the influence degree of each parameter. With the information and data collected from the experiments, we therefore establish a neural network model to provide accurate estimations. Then, by utilizing the genetic algorithm, the optimum combination of the machining parameters are determined. In this study, the optimization of the machining parameters were conducted with different defects of work pieces. The machining parameters under discussion are pressure, temperature, speed, holding time, holding force, cooling time, screw rpm, and screw pitch, while the machining performance concerned includes short shot, flash, warpage, surface roughness, and tensile strength. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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