Optimisation of precision injection moulding processing parameters and implementation of quality prediction system for LCD light guide plate

The quality of the light guide plate determines the luminance uniformity of liquid crystal display panels. Only through proper control of the injection moulding processing parameters for the light guide plate can make the precision of the light guide plate's dimensions to be improved, thus enhancing the light guide plate's optical properties. The objective of this research was first to discover the optimal combination for the light guide plate's injection moulding processing parameters. The Taguchi method was used to conduct the parameter design and select the control factors within the processing parameters that affect light guide plate quality. A confirmation experiment with a 95% confidence interval was then adopted to verify the reproducibility. At the same time, a back propagation neural network was applied to set up a quality prediction system for the light guide plate moulding. Its input layer had eight neurons, representing eight control factors. The hidden layer had five neurons. The output layer had one neuron, which was the signal-to-noise ratio of the light guide plate's luminance uniformity. By comparing the neural network's predicted values with the confirmation experiment's actual values, the system's ability to make accurate predictions could be verified.