A functional data-driven method for modeling degradation of waxy lubrication layer

Wax is a prevalent lubrication material extensively employed in various engineering applications. Understanding the degradation characteristics of the waxy lubrication layer under diverse stress variables and levels is crucial for ensuring system security and reliability. Due to the unclear mechanism governing the degradation of the waxy lubrication layer under different stress variables, existing degradation models are unsuitable for modeling waxy lubrication layer degradation data. To address this challenge, we propose a functional data-driven method leveraging dense observations of waxy degradation. Through extensive simulations and a case study, we demonstrate the superior performance and effectiveness of the proposed approach.