This paper attempts to demonstrate a systematic spectral approach for the characterization of the topographic nature of rough surfaces. Multiscale roughness characterization reveals a panoramic structure of microgeometric features of engineering surfaces, and this is of practical importance in order to include length scale consideration in real contact problems. Surfaces with different levels of root mean square (rms) roughness values were prepared using mechanical finishing processes for this study. Both optical and stylus profilometry data were recorded and analyzed to plot autocorrelation and power spectral density functions (PSDFs) at five different cutoff bandwidths (BWs). Correlation distances were estimated by choosing normalized autocorrelation declination to 1/e as well as to 0.1. In most of the cases, these distances were found to be less than 10% of the corresponding cutoff lengths. Nature of power spectrum has been analyzed and discussion extended to the estimation of bandwidth limited fractal characteristics based on specific spectral information. Power spectral densities (PSD) and their higher moments were extensively used to compute roughness parameters of functional significance such as asperity curvature, asperity density, etc. Evolution of asperity sharpness and asperity density during finishing processes was demonstrated at par with their physical significances. The intrinsic bandwidth parameter as per Nayak's definition was estimated closely to be a value of two for all cases.

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This paper proposes a wear model for polymers based on so-called mechanistic processes comprising both low cycle fatigue and abrasive wear mechanisms, which are prominent in polymer–metal sliding interfaces. Repeated elastic contact causes localized fatigue, whereas abrasive part is an anticipatory outcome of plastic contacts by hard metal asperities on to soft polymer surface. Further, presuming adhesive interactions in elastic–plastic contacts, asperity contact theories with necessary modifications were analyzed to assess load and separation for their subsequent use in elementary wear correlations. Both Gaussian and Weibull distributions of asperity heights were considered to include statistics of surface microgeometry. Finally, volumetric wear was written in terms of roughness parameters, material properties, and sliding distance. Validation was conducted extensively, and reliability of the formulation was achieved to a large extent. Experimental part of this work included several pin-on-disk tests using polyether ether ketone (PEEK) pins and 316L stainless steel disks. Disks with different roughness characteristics generated by polishing, turning, and milling were tested. Experimental results agreed well with predictions for the polished surface and with some deviations for other two surfaces. Further, fatigue to abrasive wear ratio was identified as an analytical tool to predict prevailing wear mechanism for polymer-metal tribo-systems. After examining the considered cases, it was both interesting and physically intuitive to observe a complete changeover in wear mechanisms following simply an alteration of roughness characteristics.

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