10 Benefits of Predictive Maintenance

As previously discussed, the operating time of industrial machinery and production lines translates directly into profit. Every minute gained in their activity increases the profitability of the equipment and the company as a whole. In this simple equation—more operational time equals greater profitability—predictive maintenance systems are a fundamental contributor.

Leveraging these types of tools, based on big data and artificial intelligence, it is possible to transition from scheduled maintenance to a system that addresses the true needs of the equipment. This is achieved by constantly monitoring equipment to analyze its performance not only in real time but also for future predictions, as the name suggests.

The exploitation of data in industrial activities allows for predicting what will happen in machines or lines, enabling maintenance teams to anticipate potential failures or breakdowns, thereby minimizing damage, the use of spare parts, and downtime. The application of data science, Internet of Things (IoT – IIoT) devices, Artificial Intelligence, and Business Intelligence have revolutionized maintenance operations, which are now based on reliable information reflecting current and future reality, rather than solely on the intuition or experience of operators.

Thanks to the ‘radiography’ provided by predictive maintenance systems, truly efficient management of equipment monitoring and care is now possible. Based on this, equipment lifespan can be extended, interventions can be scheduled at times with minimal impact on production, and unforeseen failures can be detected early.

Let’s look more specifically at the 10 main benefits of implementing Maintenance 4.0 models:

Real-time equipment monitoring: As briefly mentioned, being able to check the current status of machinery at any given moment allows for determining its true needs. This eliminates fixed schedules and routine tasks, enabling action only when intervention is genuinely necessary. Monitoring machines and knowing their reference parameters in real time ensures effective and efficient maintenance, based on current performance knowledge and future predictions.

Optimization of parts and spare parts: With models based on corrective and preventive maintenance, supported by fixed review and replacement periods, substitutions and interventions are often carried out unnecessarily, or when they are unlikely to be needed in the short term. Predictive maintenance, on the other hand, is based on the true needs of the machines, maximizing the use of each component, piece of equipment, and production line.

Early detection of anomalies: Knowing the status of machinery in real time also makes it possible to detect anomalies (wear, vibrations, breakages, etc.) early, which could lead to operational failures. This allows for planning repair actions in the early stages of a breakdown, or even before it occurs, preventing major breakages with extended downtime. Early detection is one of the significant advantages of predictive maintenance over preventive maintenance, which, by working with predefined inspection and parts replacement schedules, may overlook or fail to detect early faults, depending solely on chance.

Increased productivity: The preceding points lead to an increase in productivity. Knowing the status of machinery or lines in real time and the ability to detect operational anomalies early to address them in their initial stages, if necessary, allows for increased equipment productivity. With the implementation of predictive maintenance systems, machines increase their operational time as unnecessary stoppages are eliminated, and their inoperability time is reduced by enabling repair work prior to a breakdown.

Process optimization: Plant operators will be able to design strategies aimed at maximizing equipment performance, as they have constantly updated information about them and predictions of what may happen in the future.

Improved planning: Knowing what is happening and what will happen—that is, having real-time equipment status and future predictions—ensures higher levels of planning for interventions on lines or machines, necessary purchases, required human resources, enables better stock management, and allows for determining the best times (those with the least impact) to interrupt production processes.

Simplifies decision-making: With detailed real-time and future information, decision-making is simplified and more accurate, as it is based, as mentioned, on objective data, not on calendars, experience, or intuition, as in previous models.

Frees up personnel for other tasks: The automation of machinery status monitoring allows personnel to be freed up for other tasks, such as decision-making or strategy design.

Configurable alerts: Predictive maintenance systems allow for setting predefined alarms to notify of parameter alterations deemed significant for addressing process failures.

Significant savings: All the previous points lead to significant cost savings. Productivity and profitability increase proportionally to the reduction in the number and duration of stoppages; the decrease in parts expenditure, as they are only replaced when their useful life ends; or the early detection of anomalies that prevent major breakdowns, for example.

Conclusion

Having predictive maintenance systems that allow for understanding machine behavior every second and its future evolution is truly invaluable for companies. It facilitates planning, increases performance, saves costs, frees up personnel for other tasks, increases profitability, improves decision-making, and offers a long list of other benefits that enhance business productivity and profitability, making them more competitive.