Featured Whitepapers

High-performance lubricants can offer industrial plants significant savings on equipment repair and replacement, energy costs, and downtime. One way this is accomplished is by prolonging chain life. This white paper will explain how the right lubricants can double the service life of your chains, and will make you think differently about how new chains should be deployed.
Bearings are not meant to last forever; failure mechanisms are inevitable. Trying to understand what affects bearing life has produced many common misconceptions—especially incorrect assumptions about how long a bearing should last. In this white paper Andy Page will discuss the various failure modes of bearings, including the role of lubrication and fatigue. Through understanding the factors that contribute to and accelerate this process, plant personnel will gain a more realistic expectation of bearing health and lifecycles and will be well prepared to move from reactive maintenance to condition-based maintenance and thus greater reliability.
It’s difficult to replace the value of machine analysts walking the plant floor using their human senses to detect problems. Moving that expertise into artificial intelligence (AI) will take a while, but you can move sensor data today. Read this featurette to see (and hear) how NI InsightCM™ software for machine monitoring can help experts hear vibration problems from anywhere with web access just as clearly as if they were on the plant floor.
Acoustic Lubrication is an essential part of a proactive reliability program as it can reduce or eliminate machine failures due to over and under lubrication. This Infographic outlines an effective way to grease your bearings right and brings you one step closer to best practices for your lubrication program. Download your copy now!
Particle imaging, electromagnetic, ferrographic, and spectroscopic methods were used to evaluate hydraulic oil samples collected from machines known to be generating abnormal wear particles. Analytical ferrography confirmed the presence of large reworked ferrous particles and small rubbing wear particles in the oil samples. ICP emission spectroscopy was limited in its ability to detect large ferrous particles. An automated particle imaging system incorporating dual electromagnetic sensors counted the number of ferrous wear particles larger than 25μm in the oil and measured the total ferrous concentration in parts per million. The number of large ferrous wear particles (counts/ml) was found to be independent of the total concentration of ferrous particles (ppm). The ratio of large to small ferrous wear particles and their concentration revealed the severity of wear occurring in the machines. These results demonstrate the diagnostic advantage of combining magnetic and particle imaging sensors in an integrated system.

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