Assessment of the most appropriate excavation method and related equipment plays an important role in the mining and civil engineering projects. Therefore, accurate methods of estimating the ease of excavation are required. For the past three decades, various empirical predictive methods have been proposed by a number of authors. Of these, rock mass classification systems are one of the most common means of excavatability assessment. Such classification systems assign quantifiable values to selected geotechnical parameters of the rock mass. The resulting ratings are then related to ease of digging and equipment type. Despite their widespread use in practice, they have some common deficiencies leading to uncertainties in their practical applications. These deficiencies are particularly related with the existing sharp transitions between two adjacent excavation classes and the subjective uncertainties on data that are close to the range boundaries of rock classes. In this study, the basic principles of the fuzzy set theory were described and then the fuzzy set theory was applied to one of the conventional classification systems by following the Mamdani fuzzy algorithm. It was shown that the fuzzy set theory could effectively overcome the uncertainties encountered in the practical applications of conventional classification systems, and also provides more information on the obtained final ratings. To be able to check the performance of this approach in practice, case study data previously collected from operating surface mines were used. Finally, it was concluded that the fuzzy set theory could also be applied to other similar rock excavation classification schemes existing in the literature. (c) 2005 Elsevier Ltd. All rights reserved.
