In any manufacturing, petrochemical or utilities industry, production downtime is of utmost concern. The unforeseen failure of one small component can bring significant safety risks and quickly result in the loss of hundreds of thousands of dollars in lost revenue per hour.
More than fifty percent (50%) of unplanned industrial downtime is due to equipment failure. Advanced warning of an impending fault has the potential to virtually eliminate this risk, improving safety, product quality and profitability in a significant number of industries.
Advanced detection of faults can prevent a minor component failure from cascading into a major equipment outage..
Based on our vibration analysis, we were able to identify an early stage bearing failure and recommended a bearing replacement ahead of the planned maintenance cycle. This saved our client an unplanned outage that could have resulted in over $1 million dollars in lost revenue.
Failures on this critical asset caused unplanned downtime and risked spillage of hazardous substances. As seen below, bearing failure is the root cause of a significant number of secondary catastrophic failures.
An air compressor installed at a major petrochemical plant in Asia recently experienced a major unplanned outage due to a turbine failure that resulted in lost revenue of over $2 million . The VibrationLF sensor and software solution was installed and within a few days, provided an estimated time to failure that was ahead of the next planned outage. The client utilized a maintenance window to replace the faulty bearing, avoiding another $2 million in lost production.
As a result of characteristics of the vibration profile, within a few days our patented analysis was able to determine the remaining time to bearing failure based on acceptable threshold data provided by the bearing manufacturer. This advanced warning prompted a bearing replacement at a convenient maintenance interval, avoiding a catastrophic failure and unplanned outage.
Based on the vibration features, within few days, it pointed out the remaining time to bearing failure based on the threshold value for the RMS data of the bearing provided by the bearing manufacturer and hence suggested a bearing replacement well in advance. This saved our client a potential unplanned shutdown, and saved close to a $2 million dollars in otherwise lost revenue.