Prescriptive maintenance vs predictive maintenance

Prescriptive maintenance is a maintenance strategy that leverages artificial intelligence to improve asset operating conditions. Discover all the advantages

Among the different approaches to the management and maintenance of existing assets, prescriptive maintenance is the most advanced system because, in addition to predicting failures, it suggests actions and interventions to be carried out to solve unforeseen problems and ensure the correct operation of the equipment over time.

If you want to know more on this subject, you’ll find all the necessary information to understand the meaning and potential of prescriptive maintenance by illustrating some application examples and highlighting the advantages and characteristics that differentiate this strategy from traditional predictive methods.

Whichever approach you choose to manage the maintenance processes of a facility, remember that you can rely on the help of a Facility Management software to simplify the different activities and track the data related to the operation and performance of your assets. Start to experience the benefits of this system too!

What is Prescriptive Maintenance?

Prescriptive maintenance, also known as RxM, is an innovative strategy that involves the use of IoT devices and artificial intelligence technologies to collect and analyze data about the condition of an equipment and make specific recommendations for its maintenance.

At first glance, the concept of prescriptive maintenance may seem very similar to predictive maintenance. In fact, the goal of this strategy is not to just simply predict failures, but also to take into account the current conditions of machinery and components. It must also consider their historical use, to avoid problems and determine what services or repairs are actually needed.

Prescriptive maintenance has the potential to dramatically transform the way Facility Management is performed in any industry.

To better understand its meaning, it is necessary to start from the comparison with predictive maintenance as it represents its natural extension. So let’s see what the main differences are!

Prescriptive maintenance detecting potential failure events

How does prescriptive maintenance differ from predictive maintenance

Predictive maintenance is a Facility Management approach that uses data analysis and modeling to anticipate and prevent the occurrence of equipment failures or malfunctions, adopting preventive measures that are intended to reduce unplanned downtime and preserve the useful life of assets.

This particular type of maintenance uses data collected in real time by intelligent sensors to monitor the performance of resources and evaluate their general operating status. Collected data is stored in special maintenance management systems (such as CMMS, Computerized Maintenance Management System) which analyze and process this data by applying artificial intelligence algorithms, which are able to predict when error events will occur.

Prescriptive maintenance can also manages the above tasks but it takes this analysis to a higher level. In fact, it isn’t just limited to the failure forcasting or predictions but also prescribes possible solutions and provides detailed recommendations on the most effective actions to be taken.

In prescriptive maintenance, IoT technologies, machine learning and artificial intelligence are then used to analyse the operating data of the equipment, formulate different intervention hypotheses and test the results of the different actions over and over again to propose the best approach.

Of course, both preventive and prescriptive maintenance have as their main objective to minimize corrective maintenance interventions, that is, all those operations that must be performed downstream of a fault that has not been possible in any way to predict or avoid.

Application examples of prescriptive maintenance

Prescriptive maintenance has many possible uses and is already being effectively implemented:

in the automotive sector, where it helps to improve the production results of machinery, reducing the time and costs necessary for the production of complex products and components;
in the pharmaceutical sector, for the maintenance of clean rooms and controlled contamination environments. Wireless sensors and machine learning algorithms allow early identification of the conditions of use of air treatment devices and provide useful suggestions to correct problems and prevent unexpected shutdowns;
in the construction sector, through the use of maintenance software that help monitor the operation of assets and allow to detect problems suggesting the best course of action to be taken. In this sector, machine learning techniques can be used, for example, to analyze the conditions of use of the plants, predict failure events and automatically schedule the interventions of the technicians, providing the most effective solutions for solving problems.

Facility manager – performance monitoring

The benefits of prescriptive maintenance

Prescriptive maintenance shares the same benefits of predictive maintenance, but adds further capabilities to asset management because it allows you to:

harness the power of artificial intelligence and machine learning to offer a wide range of asset maintenance options and evaluate their respective outcomes.
use historical data and data collected in real time to model different intervention scenarios and suggest the best choice;
develop proactive maintenance models that help maximize equipment life, operational performance, and uptime;
anticipate problems and advise when to perform plant maintenance;
simplify and optimize maintenance operations, reducing downtime and improving efficiency and productivity.

To implement a prescriptive maintenance analysis in the simplest and most effective way possible, you can count on the help of a plant maintenance software, the only tool that through a series of integrated functions allows you to constantly track and monitor the conditions of use of your assets, and helps you to obtain a reliable information base to be used in the different maintenance approaches.