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Downtime is among the biggest challenges in industrial environments. It's significantly costly, chipping away at revenue with every minute that the machines aren't running. Even worse, downtime can affect customers and, consequently, their overall satisfaction. Plus, if the downtime is a result of an equipment fault, it can be pretty stressful for the employee. In instances such as breakage or planned maintenance, there's not a lot you can do to eliminate downtime. However, there is significant relief in the form of predictive maintenance.
The perks of predictive maintenance
Predictive maintenance can help manufacturers reduce downtime. In particular, it facilitates the monitoring of operations and recording of data for logging. This enables organisations to service equipment only when necessary, rather than through planned maintenance. Just as humans only need treatment when sick, equipment will only need tending to following real time fault detection, rather than based on age or time passed. Better still, predictive maintenance enables better efficiency, particularly among processes and production output. In turn, you can expect better customer satisfaction.
The role of IoT in predictive maintenance
Internet of Things (IoT) is a huge driver for predictive maintenance. Thus far, the sheer volume of data for predictive maintenance execution has been a significant hindrance. In particular, predictive maintenance necessitates intelligent algorithms for the storage, analysis, and processing of the copious amounts of data. IoT can facilitate the storage of terabytes of data in parallel conjunction with machine learning algorithms across several computers. By processing large amounts of data, it can therefore better predict failures. As well as this, IoT-based predictive maintenance solutions use ultrasonic and vibration sensors to collect data. However, IoT-based predictive maintenance solutions can be problematic. In particular, its implementation is no easy feat, with many companies meeting obstacles in integration. Not only that, but it has proven itself to be a lengthy process too. As with everything though, it must go through the maturation motions before we can fully reap its benefits, but the industry can remain confident that it'll eventually help industrial enterprises keep up with modern and future demands.
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