Fuzzy fault tree analysis of EVAC system based on improved SAM- FFTA with butterfly optimization algorithm

Abstract

At this stage, 3D elliptical vibration-assisted cutting(3D-EVAC) systems have proven to be a highly promising method of machining for a wide range of new materials, which can meet the requirements of ultra-precision machining. In practice, however, there are still various problems that affect its ability to achieve the desired accuracy. The functional reliability of the system should therefore be improved. Considering that the failure probability of 3D-EVAC system components cannot be obtained accurately, this paper proposes an improved similarity aggregation method (SAM) based on the butterfly optimization algorithm (BOA), called BOA -SAM. In the experiment, thirty-six events are selected and these events are aggregated by BOA-SAM. The experimental results show that BOA-SAM not only avoids the variability of the aggregation results with the relaxation factor (β) but also improves the accuracy of the aggregation results compared with SAM. BOA-SAM and FTA are connected by the center-of-mass method to form BOA-SAM-FFTA. Finally, a fuzzy fault tree analysis of the 3D-EVAC system was carried out using the BOA-SAM-FFTA method to calculate the probability of failure for each bottom event and to analyze its importance. It was found that non-uniform heating of the tool was the event that had the greatest impact on the functional reliability of the system, which offered a theoretical basis for improving the functional reliability of the system. The probability of failure of other bottom events during the experiment also can provide some theoretical guidance for the system maintenance plan .