Crack propagation in metallic mechanical components subject to cyclic loading may lead to loss of serviceability or even collapse. Often, these undesirable events may be prevented by performing appropriate maintenance activities. Nonetheless, the scheduling of these activities is highly involved due to the inherent uncertainty associated with crack propagation. In this contribution, a framework for optimal scheduling of maintenance activities within the theory of imprecise probabilities is presented. In this manner, effects of uncertainty are considered in a rational way. The proposed approach is implemented in a general purpose software for stochastic analysis. A numerical example demonstrates the applicability of the proposed framework as well as the importance of considering the effects of uncertainty.