Fuzzy logic optimization of injection molding of liquid silicone rubber.

摘要

Liquid Silicone Rubber (LSR) is rapidly growing and emerging among the materials used for injection molding. In recent years, there has been an increasing demand for high quality LSR products.; This research highlights LSR chemistry, its processing technology and tooling design since these areas are necessary to master the performance of an injection molding. It then presents an overview of the fuzzy logic language and provides a fuzzy inference system to improve the process.; Using a Design of Experiment based on the Taguchi method, the research was able to indicate the three most critical parameters of the LSR injection molding process: mold temperature, injection speed and cure time. These parameters were used as the inputs of the fuzzy inference system. The molded part weight, dimension, and visual characteristics were used as the outputs. The statistical process capability studies between the experimental runs with and without the fuzzy inference system indicated that the fuzzy logic system was found to be effective in optimizing the process. It was also found that during the course of the study the correlation between pressure, volume and temperature (P-V-T) could be very helpful in developing a more effective fuzzy inference system. This system would include additional parameters as inputs. It would also provide a closed loop control system for a self-regulating LSR injection molding.