Published by Cryotos Admin on


The impact of the Internet of Things (IoT) and Artificial Intelligence (AI) can be felt in our daily lives. It is, then, no surprise that Computerized Maintenance Management Systems (CMMS) also feel the effect of IoT and AI. Rather than compete for attention, the Internet of Things and Artificial Intelligence complement the adoption of CMMS


Connected devices provide the users with much more localized data when implemented on something like the shop floor. They help reach the minor components of a predictive maintenance system, and when this reach is coupled with AI, it takes on a whole new meaning. One of the features of using IoT devices on a large scale is the amount of information or data generated on a minute-by-minute basis. It takes something comprehensive as Artificial Intelligence to collate the data and make sense of the information in real-time.


Understanding data 


The impact of CMMS software to optimize plant maintenance and overall equipment effectiveness (OEE) has been felt for several years now; what is new is the use of IoT and Artificial Intelligence for gathering and understanding the data. 


With IoT, the data is localized, fetched from manufacturing lines and plant maintenance, providing critical information about the system’s capabilities. The availability of IoT devices has also increased the reliability of the systems because of the vast data collection points.


But when dealing with massive data, it is essential to be able to process the information efficiently as well. That is where the capability of Artificial Intelligence comes into play since it is necessary to process the data in real-time.  


IoT and CMMS

IoT makes it possible to have sensors and instruments attached to the remotest of points, relaying parameters of a particular operation to the control center. Active integration with cloud storage and cloud computing makes it possible to track information using sensors, monitors, and meters in real-time, thus ensuring that data is consumed faster than conventional systems for better decision-making.

With the latest CMMS software trying to minimize downtime and save on costs, having the latest data is crucial to the very functioning of the maintenance system. The data can produce work requests by activating specific signals when certain thresholds are breached. The feedback loop can happen in real-time, making it possible to have a functioning system that has the least reaction time possible.


Artificial Intelligence allows a certain autonomy in the data collection and action loop. The human
element is minimized, which means faster information processing and reduced human errors. Thus, reaction times become shorter, which reduces the overall cost of running the system.

AI complements human interactions speeding up the processes. However, more importantly, it creates a more extensive database that can be put to good use in the future to eliminate
or further reduce the human intervention in decision-making.

Proactive with CMMS

Most maintenance managers would wait for equipment to break down to initiate a repair adding to costly downtimes and expenses for the organization. With CMMS, it is possible to predict breakdowns before they happen. With the active use of IoT and AI, CMMS becomes even more proactive in anticipating a failure and initiating appropriate action.

What does the future hold for CMMS?

The future will see a more intense adoption of IoT and AI. The collaboration between people and machines is only going to increase. Packages like the Cryotos CMMS can be relied on to give a complete maintenance operation with minimal human intervention. Available right on hand is a maintenance system that is easy on the pocket and reduces downtimes to a great extent.

Schedule a call, and we will explain how using Cryotos CMMS can improve the productivity of your systems with prompt action, cheaper labor costs, and overall reduced downtimes




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