Investigating correlation effects of uncertain input variables in reliability-oriented sensitivity analysis for planar linkage mechanism

Time-dependent reliability-oriented sensitivity analysis (ROSA) is a potent technique utilized to assess the impact of uncertain random input variables on the time-dependent reliability of planar linkage mechanisms. However, in cases where these random variables exhibit significant correlation behavior, the existing time-dependent ROSA indices will mislead the decision-makers in distinguishing between distinct types of uncertainty effects. To tackle this problem, this study commences by examining the connotations of main and total effect indices for correlated variables. Three new time-dependent ROSA indices are proposed in this work, specifically, the individual uncorrelated effect index, the total correlated effect index, and the individual interaction effect index, which enable a comprehensive exploration of the diverse effects of correlated random variables on the time-dependent reliability of planar linkage mechanisms. Additionally, efficient computational procedure is developed by combining the envelope function method with Monte Carlo simulation to estimate the proposed time-dependent ROSA indices. Finally, the proposed approach is applied to a four-bar mechanism and a rack-and-pinion steering linkage for illustrating the necessity and superiority of exploring the correlation effects in identifying failure sources with ROSA approaches.