Mit explorativer Datenanalyse und Data Mining zu hoch effizienten polymeren Tribo-Schicht-Systemen

Abstract

Since current developments in machine building and automotive industry are dealing with the amplification of energy efficiency and sustainability of components, the reduction of friction and wear losses plays the most important key role. A further aspect of energy saving by mass reduction can be taken into account by substituting steel by lightweight metals. To fulfill these requirements, this study focuses on the development of a tribo-coating system, based on PEEK (poly-ether-ether-ketone) as a base coating material for Al substrates. The coating is applied by using laser radiation to increase the energy efficiency of the coating process on the one hand and to reduce thermal stress on the component on the other hand. Furthermore, the laser process improves the mechanical prosperties of the polymeric coating. In the first step the correlation between the coating process parameters and the resulting coating morphology accompanied by its mechanical properties and the tribological behavior was elucidated by using explorative data analysis. Here, the influence of different wear and/or friction reducing additives and their variable concentrations was also taken into account, while the tribological response of the resulting coating systems was examined and valuated under dry sliding conditions. Using data mining, the most dominant correlations between the process parameters and the tribological answer of the coating system could be found. Utilizing these findings, the process parameters for different additives in the PEEK dispersions could be optimized, and a multilayer system was established, which combines high corrosion and wear protection accompanied by a tribo-film formation resulting in low friction and an increased lifetime of the coating system.