This thesis examines solutions for condition monitoring of slew bearings, which are main components of bucket-wheel boom-type reclaimers. A detailed overview of the function of this type of reclaimer is given and the characteristics of the slew bearings are described. A sample design calculation of a slew bearing is performed to illustrate influencing factors. Extensive studies on failure modes and their probable causes are discussed. Established as well as potential ways of monitoring the condition of slew bearings are outlined. These methods of monitoring are based solely on observing the effects of wear and damage on slew bearings. The concept of data mining is introduced to assess the causes of excessive wear and damage of slew bearings. Historical operational sensor data of reclaimers is analysed using physical models. These models correspond to inverse problems that are solved by using Linear Differential Operators and their inverses. The findings of these analyses are presented in this thesis. Finally, a framework for data mining is suggested, which can be used to describe mechanisms of collecting, storing, analysing, and evaluating sensor data.