In the industrial machinery sector, early detection of potential failures is vital to avoid costly breakdowns. Atten2 has developed an innovative online oil analysis and wear debris analysis technology that stands out for its ability to detect larger particles, which often go unnoticed by conventional systems. 

Utilizing artificial vision and advanced AI algorithms, Atten2’s solution provides real-time monitoring, offering insights into the health of machinery by identifying contaminants in the oil that signal impending failures.

What sets Atten2’s technology apart is its ability to uniquely distinguish between bubbles and real particles, a significant advancement over laser-based counters that often aggregate bubbles and particles in their readings, leading to inaccurate data. The system also features advanced shape analysis, which delves deeper into particle characteristics, allowing for the identification of the root cause of wear. This capability is further enhanced by precise ISO code reporting with decimals, offering exact particle counts for more accurate assessments.

In addition to wear debris analysis, the system monitors oil degradation percentages, providing crucial data on the condition and remaining life of the oil. By delivering this information in real-time, Atten2’s technology enables users to prevent failures due to oil degradation, thereby avoiding unnecessary downtime and extending the service life of machinery. Moreover, by operating online, the system eliminates sampling errors commonly associated with traditional oil analysis methods, ensuring more reliable and consistent data.

Atten2’s cutting-edge technology not only prevents catastrophic machinery failures but also optimizes maintenance schedules, reducing downtime and extending the operational lifespan of critical industrial assets.

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