# Reliability Prediction and FMEA of Loading and Unloading Truss Robot for CNC Punch
## 1 Introduction
[PERSON] [10] proposed a risk ranking method based on fuzzy evidential reasoning and improved grey correlation degree, aiming at the deficiencies of failure mode and effect analysis (FMEA) in the identification of failure mode risk of crude oil tank of floating production storage and unloading device. [PERSON] et al. [11] conducted reliability analysis on the power and transmission system of HR50 series bending robots. Based on FMEA theory, they used the FMEA analysis method to analyze the failure mode, fault location and fault causes, and found out the weak link of bending robots. [PERSON] et al. [12] failed to consider the performance degradation of the solar wing drive mechanism and the randomness and time dependence of load in the traditional mechanical reliability analysis. Based on the uncertainty analysis and fault mode influence analysis of solar wing drive mechanism, the failure criterion is studied, and a time-varying reliability model with high precision and more consistent with the reality is established. [PERSON] et al. [13] proposed a method based on fuzzy data envelopment analysis to determine the weight of factors affecting the fault mode and analyzed the fault mode of CNC machine tools. [PERSON] et al. [14] introduced formal technology into electromechanical system FMEA, proposed an electromechanical system FMEA method based on model detection, and applied the above method to CNC machine tool feed system, successfully identified the system fault caused by the failure of the limit switch through model detection, and verified the feasibility of this method. Reliability prediction, failure mode and effect analysis have important application value in CNC machine tool and automatic production line reliability research, its value is mainly reflected in the selection of prediction and analysis methods and the accuracy of predicted results. Since reliability and fault analysis plays an important role in tracking and improving the efficiency of machine systems and subsystems [15], it is necessary to consider reliability prediction and FMEA in a comprehensive way. However, in the above literature and research it can be found that, at present, in the relevant reliability studies, most scholars often only carry out reliability prediction or failure mode and impact analysis for a product alone, and do not combine FMEA with predicted results, and there is a lack of reliability prediction results verification. For the loading and unloading truss robot for CNC punch, there is not a complete set of reliability research methods, let alone the reliability research case of the loading and unloading truss robot for CNC punch. Therefore, it is very important to combine reliability prediction with failure mode and impact analysis and verify the predicted results. Based on the loading and unloading truss robot for CNC punch in the automatic sheet metal production line, this paper studies its reliability and proposes a new reliability prediction method. By establishing the reliability model of the loading and unloading truss robot for CNC punch, using the component counting method and fuzzy theory to predict the failure rate and mean time between failures of each system, to find out the weak link, and then according to the on-site fault data of the loading and unloading truss robot for CNC punch FMEA analysis, verify and determine the weak link. Finally, the reliability requirements of each subsystem of the loading and unloading truss robot for CNC punch are clarified through reliability distribution.