Research on Prediction of Press-Assembly Quality Based on Grey Markov Model

It is very important to predict press-assembly quality by analyzing the massive quality data collected during high-precision servo mechanism assembly. Based on the relationship between the press-assembly force and quality of the high-precision servo mechanism, a method of predicting the press-assembly quality based on gray Markov model is proposed in this paper, and the press-assembly dataset of high-precision servo mechanism assembly is dealt with. Firstly, the system cloud gray prediction SCGM(1,1)c model is established for initial prediction; then, the Markov chain model is applied to upgrade the initial fitting accuracy to improve the prediction accuracy; after that, the prediction effects of gray model, system cloud gray model and gray Markov model are compared and analyzed through experiments. Experiments show that the gray Markov model has higher prediction accuracy and stability; finally, the outlier detection method of press-assembly force is studied to find out the control boundary value and define the control range of press-assembly force. The press-assembly quality prediction based on the grey Markov model provides a new method for that of the high-precision servo mechanism.