What is proactive maintenance?

Organizations implementing proactive maintenance strategies typically combine aspects of different asset maintenance philosophies into a single approach that suits their needs.

Effective proactive maintenance strategies begin with detailed maintenance plans that rely on historical data. Assets are then prioritized based on how critical their functionality is to core business processes and how likely their failure would be to cause unplanned downtime.

This modern, data-driven approach helps teams identify potential causes of equipment failure earlier than in the past and intervene before costly emergency repairs are necessary.

Typically, proactive maintenance programs rely on a computerized maintenance management system (CMMS), a software solution that creates digital workflows, automates work orders and increases asset uptime.

Successful proactive maintenance programs are typically based on four foundational capabilities:

• Condition monitoring: Condition monitoring (CM) is an approach to asset maintenance that relies on real-time data to assess asset health and perform condition-based maintenance to prevent breakdowns. Typically, CM involves continuous data collection from IoT sensors that have been affixed to various asset parts and components. These sensors can detect anomalies in pressure, temperature and vibration levels. CM is a critical tool in identifying potential issues and resolving them before they result in equipment failure.
• Predictive analytics: Predictive analytics is the practice of analyzing historical data related to asset performance and health. It then compares this information with real‑time data collected by IoT sensors. Using machine learning (ML) algorithms, predictive maintenance tools can help maintenance teams spot trends in asset performance that indicate problems before they become catastrophic. Predictive analytics helps maintenance teams maintain assets in a way that minimizes unnecessary maintenance tasks while still optimizing performance and extending asset lifecycles.
• Root cause analysis: Even with the most advanced proactive maintenance tactics, asset failures occur. When they do, root cause analysis (RCA)—the practice of identifying the underlying cause of an asset failure rather than focusing on its symptoms—is critical to preventing future disruptions. By isolating and resolving the root cause of an equipment failure, maintenance teams can prevent the same issue from recurring, often resulting in continuous improvement of their overall maintenance practices.
• Computerized maintenance management system (CMMS): A CMMS is a software platform that automates and enhances an organization’s core maintenance operations. Modern, advanced CMMS tools help organizations apply all the cutting‑edge technologies to their asset maintenance programs in a comprehensive way. A strong CMMS can track asset location, health and performance. It can automate work orders and manage complex maintenance schedules. It also tracks key performance indicators (KPIs) such as uptime and maintenance costs.

Organizations typically rely on five core types of proactive maintenance, mixing elements of each until they find the right combination for their maintenance approach. Here’s a closer look at each one.

Preventive maintenance is an asset maintenance approach that focuses on preventing equipment failures by proactively maintaining assets before parts degrade or break.

Preventive maintenance scheduling is critical to proactive maintenance programs, enabling maintenance teams to schedule routine maintenance tasks like cleaning and lubrication more efficiently.

By establishing a rigorous preventive maintenance schedule that is built on insights from CM and predictive analytics, proactive maintenance programs help prevent unexpected asset failures and unplanned downtime.

Predictive maintenance is a type of proactive maintenance that relies on predictive analytics and machine learning. It uses data collected by IoT sensors to predict when equipment, parts or components are likely to fail.

Predictive maintenance is a largely data-driven approach to asset maintenance, enabling technicians to repair assets in a way that helps avoid catastrophic failures and unplanned downtime.

Condition-based maintenance (CBM) combines aspects of preventive and predictive maintenance by scheduling maintenance activities when pre-defined thresholds for asset condition are crossed.

For example, a team of technicians working with CBM would monitor various aspects of an asset. They would configure their CMMS to trigger a work order when an IoT sensor reached a certain temperature, lubrication level or vibration frequency. This approach helps optimize resource allocation and prioritize maintenance activities for where they are most needed.

Reliability-centered maintenance (RCM) is a maintenance approach that focuses on an asset’s overall reliability, integrating predictive and preventive maintenance tactics into its upkeep to minimize the likelihood of asset failure.

Typically, RCM aligns more closely with business operational priorities like cost and resource allocation than other proactive maintenance approaches. As a result, it helps teams focus on maintaining the critical assets essential to business functionality.

Automated maintenance, also known as IoT-enabled maintenance, is the most technologically advanced form of proactive maintenance. It relies heavily on new technologies like artificial intelligence (AI), ML and IoT for its core functionality.

Automated maintenance approaches leverage real-time data integration and AI workflow automation from a centralized CMMS to manage multiple assets without manual intervention. Although it’s still new, automated maintenance approaches have already been shown to significantly streamline maintenance processes, establish more cost-effective practices and increase operational efficiency.

Enterprises turn to proactive maintenance strategies for various reasons. They typically seek to leverage modern, digital tools and technologies to increase operational efficiency.

Here’s a look at some of the most popular benefits of implementing an effective proactive maintenance strategy:

• Reduced downtime: Businesses that apply effective proactive maintenance can detect potential issues sooner and resolve them before they result in a costly breakdown. According to a recent report, the average hourly cost of downtime exceeds USD 300,000 for most firms and can cost as much as USD 5 million for some.¹
• Lower maintenance costs: While proactive maintenance strategies do require a significant upfront investment in technology to get off the ground, they help maintenance teams reduce the overall cost of their maintenance activities over time. Relying on the latest technologies and techniques to repair business-critical assets before they break helps extend asset lifespans, improve asset performance and lower the likelihood of unplanned downtime.
• Increased reliability: Increasing equipment reliability is one of the most important outcomes of any maintenance program. Proactive maintenance strategies help maintenance teams reduce malfunctions and increase asset functionality over time, making the assets an organization relies on for its core business processes more high-performing and dependable.
• Enhanced safety: Taking a proactive approach to maintenance not only improves asset performance and functionality, it also greatly reduces the likelihood that workers will be injured performing regular inspections and routine maintenance tasks. When predictive and preventive techniques are incorporated into asset management programs, assets are less likely to malfunction in a way that can cause a dangerous situation for technicians.
• Improved workflows: Relying on a CMMS to centralize maintenance data, perform planned maintenance and automate work orders helps standardize maintenance efforts and improve overall workflows for maintenance programs. Evolving maintenance procedures from outdated, manual processes to streamlined, automated ones helps increase administrative efficiencies and reduces the likelihood of human error.
• Data-driven decision-making: IoT sensors allow organizations to gain visibility into asset performance in real-time and compare it with historical data. With a CMMS and a proactive maintenance strategy, maintenance managers can leverage metrics to develop more informed and comprehensive maintenance plans for critical assets. They can also time repairs to align with business needs and support overall asset health.
• Longer asset lifespans: Proactive maintenance strategies help extend asset lifespans by establishing rigorous, data-driven maintenance plans for asset upkeep and tracking asset health meticulously with real-time data. Over time, this approach helps organizations increase their capital savings and obtain a stronger return on their investments in physical assets.

Proactive maintenance helps organizations of all sizes and across a wide range of industries transform outdated maintenance approaches into newer, more data-driven and technologically advanced ones.

Here’s a look at how five different industries use proactive maintenance practices.

The manufacturing industry relies heavily on large, expensive assets that automate complex processes, like the ones that transform raw materials into finished products like steel, textiles and pharmaceutical goods.

Proactive maintenance procedures managed on advanced CMMS platforms can gather and instantly analyze data from IoT sensors. They can also alert maintenance teams when vibration levels or equipment temperatures pass preset thresholds, triggering a work order.

Power companies rely on condition-based maintenance to monitor the temperature, pressure and other aspects of asset health and performance in wind turbines and hydro-electric dams.

Maintaining large, expensive assets such as turbines and dams is safer and more efficient due to modern CMMS tools that detect deviations in performance metrics and automatically assign technicians.

As trains increase in speed and their control systems become more complex, predictive maintenance plays a key role in keeping passengers safe. It analyzes real‑time IoT sensor data from train components and rail equipment and continuously compares it with historical data.

This new, data-driven approach to maintaining and managing train cars on the sprawling rail networks upon which they travel helps reduce disruptions, enhance safety procedures and increase asset uptime.

Preventive maintenance schedules for building maintenance are helping facilities managers make more informed decisions about how they inspect and maintain a wide range of complex assets. These assets include heating, ventilation and air conditioning (HVAC) systems, elevators and warehouses.

Preventive maintenance activities help technicians perform regular inspections of assets and replace critical parts before they result in equipment breakdowns, making facilities safer and more comfortable for occupants.

Advanced CMMS platforms and other proactive maintenance tools are transforming smart manufacturing (SM), which uses integrated technologies in complex manufacturing processes.

A CMMS tracking a smart manufacturing machine can spot when its performance deviates from preset parameters and automatically schedule a part or component to be replaced. Automation is helping reduce human error and streamline complex workflows at the enterprise level across the smart manufacturing maintenance landscape.