Calibration interval optimization and calibration conclusion risk analysis on automatic test system

In this paper, we put forward an optimization strategy of the determination of the calibration interval for ATS. Based on our information flow model of metrology chain, the correlation matrix of fault and calibration is established, and then the measurability contribution rate of ATS is calculated with this model. According to the gray forecasting model, the calibration interval of individual instrument is determined and with the measurability contribution rate we can finally work out the calibration interval of the ATS as a whole. Compared with the traditional methods, our method is more scientific and feasible, taking influential factor of each instrument into consideration, and adjusting with the latest data. At last, we analyze the affecting factors of calibration conclusion risk, which provides some guidance to reduce the misjudgment probability and improve the reliability in calibration work.