Machinery Lubrication

Machinery Lubrication November-December 2018

Machinery Lubrication magazine published by Noria Corporation

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For many years, the process of analyzing lubricants, coolants and fuels to improve the reliability and maintenance of machines has remained relatively unchanged. Fluids typically are sampled from an asset on a regular cadence and sent to a lab to be processed. e results are interpreted by experts or simple rules-based analysis, and a report is returned. e asset owner must then use the report to decide whether to take action or continue normal operation. Although laboratory analysis produces extremely valuable data, the process can become somewhat cumbersome and may not provide a consistent spectrum of deep insights that asset owners need to increase performance and reliability. Today, the rise of artifi cial intelligence (AI) and machine learning is allowing the aggregation of all lab data into a single platform as well as the ability to look at assets in a deeper and more granular way. is is resulting in greater insight that can deliver better precision, consistency and lead times than previous methods. Fluid Analysis History Fluid analysis was fi rst pioneered by the rail industry in the 1940s. Railroads quickly realized the analysis of fl uids could proactively identify potential issues with diesel engines, air compressors and other rail equipment. By the 1960s, the analysis of industrial lubricants, coolants, fuels and other fl uids by commercial laboratories had become common. e data delivered to industry by these laboratories facilitated the transition away from time-based maintenance toward condition- based maintenance for critical components. Oil analysis is now being utilized for a number of benefi ts, including root cause analysis, preventive maintenance, condition-based oil changes and proactive component change-outs. For new equipment, it can be used as a supplement to the data generated by sensors and onboard computers. On legacy equipment with no telematics, it serves as one of the only insights operators have for asset health. e practice of oil analysis has become widely utilized and recognized as valuable across all industrial sectors, including agriculture, aviation, energy, transportation, mining, manufacturing, and oil and gas. Current Data Analysis Options Laboratories and industrial companies currently utilize oil analysis data in a number of diff erent ways. While each of the following methods has benefi ts, 6 | November - December 2018 | www . By Eric Holzer, Uptake COVER STORY Supercharging Oil Analysis with AI

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