Statistical model for predicting friction coefficient and wear of duplex CrN/DLC and nano-multilayer DLC-W coatings using ANOVA

Abstract

Abstract Diamond-like carbon (DLC) coatings are gaining wider attraction due to their excellent mechanical and tribological properties. This research presents statistical models to predict the wear and friction coefficient of duplex CrN/DLC and nano-multilayer DLC-W coatings through analysis of variance (ANOVA). The coatings were deposited using a hybrid PVD/PECVD system onto carburized and quenched martensitic valve tappets. Tribological tests were conducted on the coatings in a ball-on-plane configuration using a reciprocating slide on an Optimol SRV® v4 device under dry conditions. ANOVA and regression analysis were employed to analyze the wear rate and coefficient of friction (COF), leading to the development of a prediction equation. The results indicated that both applied load and operating temperature had nearly equal influence on the COF and wear of the coatings. The reliability of the proposed statistical models was approximately 92–96% for duplex CrN/DLC and 90–97% for nano-multilayer DLC-W. These models are applicable only to the tested parameters within the deformation region. They can be used to predict the tribological operating conditions for the duplex CrN/DLC and nano-multilayer DLC-W coatings, helping to prevent premature failure.

Keywords

• Duplex CrN/DLC
• Nano-multilayer DLC-W
• Wear
• Friction
• ANOVA
• Regression analysis