Grease plays a vital role as both a lubricant and a functional component of bearings, especially in high demand applications such as wind turbines and large engines. These systems operate under challenging conditions, including variable speeds, extreme loads, and harsh environments, which accelerate grease degradation and compromise bearing performance. Grease failure modes, such as oxidation, contamination, oil bleed, and loss of consistency, directly impact the lubrication quality and, consequently, the health of the bearing. Understanding and mitigating these failure modes are essential to ensure equipment reliability, reduce downtime, and extend component life. Failure mode analysis highlights common issues affecting grease performance. Oxidation leads to increased acidity and viscosity changes, while contamination by water, dirt, or metal particles reduces the protective capabilities of grease. Excessive oil bleed or hardening compromises its ability to maintain an adequate lubrication film. These failure mechanisms contribute to bearing damage, such as wear, fatigue, and overheating, often culminating in costly failures. Grease analysis serves as a key diagnostic tool to monitor these failure modes. Analytical techniques, including Fourier Transform Infrared Spectroscopy (FTIR), consistency testing, and wear particle analysis, provide detailed insights into grease degradation, contamination, and additive depletion. By integrating grease analysis with operational data such as bearing temperature, vibration, and ultrasound readings, a more comprehensive understanding of system performance can be achieved. For instance, a rise in bearing temperature may indicate lubrication starvation or grease hardening, while ultrasound signals can detect early-stage wear linked to insufficient grease distribution. This paper explores the integration of failure mode analysis, grease testing, and operational monitoring for proactive maintenance in wind turbines and large engines bearings. Case studies illustrate how correlating grease analysis results with operational parameters enables early detection of issues and optimizes maintenance strategies. In wind turbines, grease analysis reveals trends in contamination and wear, while vibration and temperature data validate the impact on bearing health. By addressing grease as a critical component of the bearing system, this session provides actionable insights for enhancing lubrication strategies, preventing failures, and improving overall system reliability.
Attendees will gain the knowledge needed to adopt a data-driven approach to lubrication and asset management.

Reliability Manager, Condition Monitoring Engineer, Researcher and consultant in Condition Monitoring and Predictive Maintenance in the power generation, manufacturing and wind energy industries, among others.
Extensive knowledge of the Predictive Maintenance markets of Europe and the Americas, full customer technical support, focused on improving plant reliability through oil condition monitoring, lubrication best practices and digital transformation strategies.