What is preventive maintenance?

Preventive maintenance (PM) is a proactive approach to maintenance that helps prevent unexpected equipment failures. PM is considered a type of planned maintenance and is a key component of effective facilities management.
 

Also referred to as preventative maintenance, PM covers a wide range of regular maintenance activities. It helps industrial organizations avoid repair costs and inefficiencies associated with unexpected breakdowns and equipment downtime. Examples of preventive maintenance tasks include cleaning and lubricating equipment and more extensive tasks such as repairing critical assets or replacing parts.

At a higher level, preventive maintenance plans might also involve upkeep of the production facility. These tasks might include regular inspections of the HVAC system, electrical systems and lighting.

Today, maintenance teams can use automation, the Internet of Things (IoT), data analytics and artificial intelligence (AI) to streamline maintenance workflows. These technologies allow organizations to preemptively resolve issues before they require costly repairs or cause production disruptions.

There are five types of preventive maintenance strategies within PM programs. While each type is built upon the concept of planned maintenance, they are uniquely organized and scheduled to prioritize different business operation purposes.

Usage-based maintenance considers an asset’s usage metrics or exposure to environmental conditions to determine the maintenance schedule. For example, delivery trucks might require oil changes every thousand miles.

Calendar- or time-based maintenance occurs at scheduled time intervals, often according to manufacturer recommendations. For instance, a maintenance technician might perform weekly maintenance on critical equipment to ensure peak production levels and increase uptime.

Condition-based maintenance uses monitoring tools to collect equipment performance data and determine when preventive maintenance work is necessary. This type of maintenance relies on algorithms, machine learning and AI analysis to identify patterns and anomalies in the data that might indicate a maintenance issue.

Predictive maintenance uses condition monitoring tools, historical data and advanced analytics to identify, detect and address issues as they occur in the production cycle, and predict the potential future state of equipment. It optimizes equipment lifespan and performance by continually assessing its health in real time.

Prescriptive maintenance is a more proactive maintenance strategy than even predictive maintenance. Where predictive maintenance identifies potential failures, prescriptive maintenance also provides specific corrective maintenance actions to prevent them from happening in the first place.

There are several advantages of preventive maintenance programs. Benefits include:

One key element separates preventive maintenance from reactive maintenance: timing. Reactive maintenance adopts a “run-to-failure” policy where maintenance only occurs when a piece of equipment stops working. Then, the maintenance team must complete the repair as quickly as possible to prevent further downtime.

Reactive maintenance procedures can easily become far costlier than preventive maintenance, which attempts to anticipate equipment failures and take corrective maintenance action before mechanical breakdowns occur. Consider the example of car maintenance. If a car doesn’t undergo routine maintenance procedures such as oil changes, it might sustain severe engine damage over time, which demands far more extensive and expensive repairs.

Many PM strategies include enterprise asset management (EAM) systems to maintain and control assets and equipment. One aspect of EAM is a computerized maintenance management system (CMMS). A CMMS can help automate work orders and workflows, schedule labor and manage materials.

Today’s equipment and facilities are increasingly smarter and more connected due to the Internet of Things (IoT) and artificial intelligence (AI). More extensive data collection—made possible by IoT and AI—can give organizations valuable insights to improve asset and operational reliability.

AI's role will continue to grow. An IBM Institute for Business Value study found that  71% of executives say gen AI fundamentally changes how they will manage assets. The same study found that 72% of executives say it increases the strategic value of physical asset management.

By combining automation, IoT data, analytics and AI, leading CMMS software can now do more than just react to maintenance issues. It can help teams take predictive and preventive maintenance action, extending asset lifespans, controlling costs and optimizing resource efficiency.