The management of maintenance activities for industrial facilities or complex infrastructures plays an increasingly strategic role, and minimizing malfunctions has never been more achievable. Let’s explore how predictive maintenance can improve processes and, most importantly, minimize the impact of errors, slowdowns, or even shutdowns!
Types of Maintenance: A Comparison
There are three main methods for managing equipment failure: corrective, preventive, and predictive maintenance.
Corrective maintenance is applied when a failure has already occurred. While this type of maintenance doesn’t require prior planning, it leads to production disruption during the repair process, causing losses from the time spent addressing the issue and the costs incurred in fixing the problem.
Preventive maintenance, on the other hand, involves scheduled activities aimed at keeping the system running at peak performance. It is certainly more effective and cost-efficient than corrective maintenance, but it is still not the optimal solution. The ideal approach is predictive maintenance. Why? Simply put, predictive maintenance ensures that equipment only shuts down just before an impending failure, reducing downtime and minimizing maintenance costs compared to preventive maintenance.
How Does Artificial Intelligence and Predictive Maintenance Work for Automation?
Predictive maintenance utilizes Artificial Intelligence (AI) to evaluate and monitor machine performance in real-time. This is made possible by the Internet of Things (IoT), which enables the connection between different analysis systems and data sharing. By doing so, the necessary information is gathered to identify vulnerabilities in the system, predicting issues that could cause service disruptions or equipment malfunctions.
How Do Companies Benefit from Predictive Maintenance?
Studies show that predictive maintenance programs can lead to a tenfold increase in ROI, a 25-30% reduction in maintenance costs, a 70-75% decrease in failures, and a 35-45% reduction in downtime (Source: Automationtomorrow). This is why it is essential to anticipate service disruptions before they occur by managing data discovery and forecasting/prediction tasks through advanced machine learning techniques. These methods help create tailored solutions to optimize the efficiency of production processes.
For more information on predictive maintenance and how it can maximize your business efficiency, contact our experts!
