Enhancing tolerance stack-up analysis with variable-dependent admissible limits

This work introduces the concept of variable-dependent admissible limits for tolerance stack-up analysis, where limits adapt based on geometrical and non-geometrical variables. Unlike traditional methods that assume fixed limits, the proposed approach integrates these dependencies into both variational and Monte Carlo analyses, enabling broader tolerances while maintaining functionality. A case study from the automotive sector demonstrates the methodology's effectiveness. This innovation shifts tolerance analysis from a purely geometrical to a functional domain, improving accuracy, reducing costs, and supporting compact and safe designs in industrial applications.