New developments in engineering and science in systems involving surfaces (friction, wear, contact deformation, reflection, electrical conductivity and resistance, heat transfer, tolerances and fits, etc.) require more comprehensive characterization of their micro- and macro-geometrical texture. Previous experience exhibits the fact that a statistical description of a surface by means of the first and second moment of the ordinate probability density distribution such as c.l.a. or r.m.s. and other parameters is not adequate. This paper discusses the more recent developments of surface characterization, considering a two- and/or three-dimensional random process by means' of the auto- and cross-correlation functions, power spectra, and the slope probability distribution parameters. A representative number of surfaces manufactured by a variety of metal-removal processes have been investigated in order to achieve, first, the differentiation of the surfaces with the same c.l.a. and r.m.s. values, and second, the separation of the periodic and random components in the surfaces. It is shown that the new techniques may disclose the differences in the internal structure of the surfaces. The elementary correlation functions, which may describe analytically the types of real surface profiles, are employed for the design of the surface topography system based on the correlation lengths and correlation wavelengths. On a number of practical examples there is shown the applicability of the proposed surface classification which is independent of the surface generation process. The theoretical approach and the experimental confirmation of the conclusions represent basically a new tool for comprehensive surface characterization. However, it should be considered that such a description requires a data requisition and processing by means of digital or special statistical computers. This circumstance does not affect the basic research work, but it is impractical for workshop application. Therefore new parameters and measuring methods have been developed to make the use of more comprehensive surface characterization methods possible in practice.

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