Condition monitoring is an important tool in the predictive maintenance of machines. By collecting and analysing certain signals from motors, developing faults and inefficiencies can be identified, and unplanned downtime can be avoided.
There are a number of different signals that can be taken into account when monitoring mechanical assets. Traditional condition monitoring was mostly based around vibration analysis, but more modern, innovative techniques focus on MCSA (motor current signature analysis).
Simply put, condition monitoring uses a number of signals to predict three things. First, whether an asset will break. Second, how it will break, and third, the time you have to fix or replace the asset before it functionally fails. Armed with this information, you can schedule maintenance at a time that suits production.
The ability to plan downtime in an industrial environment is hugely beneficial, as the true cost of unplanned downtime due to a failed asset is often wildly underestimated.
Apart from the avoidance of downtime due to machine breakage, condition monitoring contributes to a well-run plant in a number of other ways:
Predictive maintenance using condition monitoring allows you to maximize the return on investment in your mechanical assets. By monitoring the actual condition of your machine, you can inspect, fix or replace the machine only when it's necessary, and not before.
Conversely, preventive maintenance requires the replacement of all machines after a certain period of time (or number of running hours) regardless of whether they have started to show signs of a fault. By keeping your machines in action until it's necessary to change or replace them, you can get more out of your machine, improving TCO (total cost of ownership), and maximize initial capital ROI.
In a scenario where there has been a breakage, maintenance engineers are able to act faster using condition monitoring. Different motor signal patterns are indicative of different developing faults in the asset the motor is driving—so condition monitoring will help the maintenance engineer to focus on the right fault, and not waste time checking parts of the asset that are not broken. This ultimately makes the maintenance engineer faster and more effective at his or her job.
By being able to determine when an asset will break, maintenance personnel can ensure safer work practices. Depending on the nature of the asset, a breakdown could be quite destructive, and could pose a threat to the safety of employees working around the asset. By using condition monitoring, maintenance personnel can plan maintenance before a motor break poses a potential threat to safety.
SAM4 by Semiotic Labs uses motor current signature analysis, meaning it can also detect when a motor is beginning to run less efficiently. As a result, you can focus your efficiency improvements on specific motors.
Statistically, 20-40% of your maintenance personnel are likely to retire in the next 5 years. That means your ability to react to future unplanned downtime could suffer. SAM4 helps your maintenance team avoid unplanned downtime and maximize plant productivity in the future.