K. Bobzin, C. Kalscheuer, RWTH Aachen University, Aachen, Germany
Physical Vapor Deposition (PVD) technology and coatings are integral part of today’s products and production routes. Efficient process development, coatings tailored to specific applications, and performance prediction of coated components are crucial topics. Regarding process and coating development, experimental and iterative approaches are still common. However, synergies between experiment and simulative capabilities gain increasing importance. Regarding performance prediction of coated components, the interplay between experiment and simulation becomes even more important.
Within this presentation, tribological nitride, oxide and oxynitride coatings as well as self-lubricating coatings for tools and components are addressed. The deposition technologies span from magnetron sputtering over arc-PVD to gas flow sputtering. The field of applications reaches from cutting and forming tools until machine elements such as gears and chains.
Prediction of coating properties and coating performance in applications cannot be solved solely by physics-based approaches up to now. Within this context, approaches to determine coating properties from process parameters by data-driven methods are shown. Regarding performance prediction, greybox models that combine physics-based models and data-driven methods are very promising. Current research on greybox models for wear prediction of cutting tools is presented.