Markov models find optimum inspection intervals for phased deterioration of monitored complex components in a system with severe down time costs. The number of (pseudo)-phases can be increased, but in most cases, simple models tracking actual states and their perception by the user will suffice, because of paucity of data and near-constant rates. The matrix is cyclic; it includes renewal and regression to earlier states, simplifying solution and matching observation. An example involves roller bearings in paper mills with three phases, no defect, possible defect, and final deterioration towards failure. In the last phase, continuous monitoring is used.