MSPC And Its Application In Injection Molding

Because of the excellent performance of injection parts, they have been used widely from daily life to high-precision application such as instruments, automobiles and aerospace equipments etc.. So higher accuracy of injection parts is required due to their application in high-precision field. At the same time, the requirement of processing parameters is more and more demanding. So SPC (statistical process control) has been introduced in injection molding to monitor and control the injection processing. However, the traditional SPC is mainly utilized to control only one variable. SPC charts only reflect the information of one variable either for processing parameters or for products parameters. It is not enough for injection molding because the parameters of injection molding are mutually associated.MSPC (multiple statistical process control) in injection molding is used to monitor and control the injection processing parameters and injection parts performance with MSPC methods. The dimensionality of parameters can be reduced and injection process will become easier to be monitored and controlled when MSPC methods are used in injection molding. Multiple statistical control charts can describe many parameters in one control chart using the curve. So it brings many benefits for operators to monitor injection process and experts to analyze injection processing parameters.It includes five aspects in this paper.1. Compare the various control charts in SPC, and match the different control charts with different situations. Find the most appropriate control charts when they are used in injected products control.2. Establish a relationship between processing parameters and products performance with a multiple linear regression equation. The multiple regression equation can predict the thickness of injected products by using the multiple regression method. And the equation is verified by the analysis of variance and analysis of residual.3. On the basis of central composite design, this paper discusses the non-linear connection in pressure, molded temperature and thickness of parts in injection. And based on experiments, a non-linear multiple regression equation is established to predict the thickness of injected parts.4. Analyze the connection of barrel temperature in different zones with PCA methods. And describe many parameters in one chart using MSPC control chart methods. It is very beneficial for operators to monitor and control the injection processing.5. Establish the suitable MSPC software system in injection molding. It includes eight components in the software system to complete different functions.The study in the paper is only the preliminary study in this field. It provides the important reference for the future jobs.