Study on the Prediction of Complex Equipment MTBF DGM~((p/q))(1, 1) Model Based on the Small Sample

摘要

Mean Time Between Failures (MTBF) is an important indicator of the reliability of complex equipment, it has important influence and significance on the design, production and use of complex equipment. It represents the quality, the ratio and the failure time of complex equipment products at the same interval period. For complex equipment, it is difficult for us to obtain larger sample reliable data by sampling statistics like mass production products. There are some defects when we are using the traditional statistical prediction methods to study the prediction of complex equipment MTBF based on small samples. In this paper, we tried to use the DGM~((p/q))(1, 1) model to predict the MTBF of complex equipment based on small samples. We made a study based on the MTBF prediction of a CNC machine. Compared with the MTBF prediction results of the traditional Welbull method and the classical GM (1,1), DGM (1,1) model, the prediction of complex equipment MTBF DGM~((p/q))(1, 1) Model is more effective.