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 System (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 packages.
Connected devices provide users with much more localized data when implemented on something like the shop floor. They can also facilitate access to the minor components of a predictive maintenance system. When combined with AI, this capability takes on a whole new meaning. One of the key advantages of using IoT devices on a large scale is the amount of information generated on a minute-by-minute basis. However, it takes something as comprehensive as Artificial Intelligence to collate the data and make sense of the information in real time.
CMMS software has been optimizing plant maintenance and Overall Equipment Effectiveness (OEE) for several years. What is new is the use of IoT and Artificial Intelligence for gathering and understanding data.
IoT provides localized data fetched from manufacturing lines and plant maintenance, which can provide critical information about the system's capabilities. The availability of IoT devices has also increased the reliability of the systems, thanks to the vast number of data collection points.
However, when dealing with massive data, it is essential to process the information efficiently as well. This is where the capabilities of Artificial Intelligence come into play because processing the data in real time is necessary.
IoT makes it possible to attach sensors and instruments to remote points, relaying the parameters of a particular operation to the control center. Active integration with cloud storage and computing makes it possible to track information using sensors, monitors, and meters in real time, which ensures that data is consumed faster than conventional systems, enabling better decision-making.
As the latest CMMS software tries to minimize downtime and save on costs, having the latest data is crucial to the system's functioning. The data can generate work requests by activating specific signals when certain thresholds are breached. This feedback loop can happen in real-time, allowing for a functioning system with the least possible reaction time.
Artificial Intelligence allows for a certain degree of autonomy in the data collection and action loop, minimizing the human element. This results in faster information processing and reduced human errors, ultimately leading to shorter reaction times and lower overall costs for running the system.
AI complements human interactions, speeding up processes and, more importantly, creating a more extensive database that can be leveraged in the future to reduce or eliminate the need for human intervention in decision-making.
Most maintenance managers typically wait for equipment to break down before initiating a repair, which adds 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.
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.