Assessment of cylindricity has been traditionally performed on the basis of cylindrical crowns containing a set of points that are supposed to belong to a controlled cylinder. As such, all sampled points must lie within a crown. In contrast, the present paper analyzes the cylindricity for wear applications, in which a statistical trend is assessed, rather than to assure that all points fall within a given tolerance. Principal component analysis is used to identify the central axis of the sampled cylinder, allowing to find the actual (expected value of the) radius and axis of the cylinder. Application of k-cluster and transitive closure algorithms allow to identify particular areas of the cylinder which are specially deformed. For both, the local areas and the global cylinder, a quantile analysis allows to numerically grade the degree of deformation of the cylinder. The algorithms implemented are part of the CYLWEAR <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">copy</sup> system and used to assess local and global wear cylinders.