Reactive maintenance, sometimes referred to as corrective maintenance, refers to an equipment maintenance strategy where maintenance is only performed once an asset has broken down. This approach is based on the belief that costs sustained during asset downtime or because of necessary repair are typically lower than that of maintaining an overall maintenance program. Along with preventive and predictive maintenance, reactive maintenance is one of the most widely used maintenance strategies today.
While both preventive and predictive maintenance strategies adhere to regular maintenance schedules to avoid asset malfunctions, reactive maintenance only prescribes repairs once an asset has failed. An asset is defined as something that is useful or valuable to an organization. The term can include both physical and non-physical assets such as infrastructure and equipment, capital and people.
Preventive and predictive maintenance are both considered proactive maintenance strategies and are best suited to organizations that own complex assets and have capital they are ready to invest in an overall maintenance program. Reactive maintenance, on the other hand, is best suited to organizations with low-cost, non-critical assets that won’t interrupt normal business processes when they break down.
There are three different types of reactive maintenance.
Emergency maintenance: Emergency maintenance is a type of unplanned asset maintenance that is deployed when a piece of vital equipment has broken down. Because of the priority given to repairing a piece of equipment with emergency maintenance work, it is common for this strategy to result in interruptions and delays.
Breakdown maintenance: Like emergency maintenance, breakdown maintenance is an unplanned response to an asset suddenly needing to be repaired. Due to the unexpected nature of breakdown maintenance, it is common for it to be both expensive and time consuming.
Run-to-failure maintenance: Run-to-failure maintenance is a maintenance strategy that deliberately allows assets to be run until they break. In some cases, a replacement asset has already been purchased and is ready to be installed. The strategy is only effective with pieces of equipment that can be replaced or repaired swiftly without shutting down production for a significant amount of time.
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Like any widely used maintenance approach, there are pros and cons to running a reactive maintenance strategy. While fine for low cost, low priority assets, reactive maintenance can have a negative impact on the lifecycles of larger more complex assets—typically the ones organizations rely on for normal business operations.
Requires little or no planning: When you’re reacting to a breakdown instead of anticipating and preparing for it, you don’t need to take time to train and prepare your staff.
Minimal cost of implementation: All the financial resources required to run a reactive maintenance strategy are only used when an asset has broken, so there’s almost no upfront cost.
Fewer full-time employees needed: Reactive maintenance isn’t labor-intensive until an asset breaks, freeing up staff and resources for other business purposes.
No regular stoppages: Since you aren’t routinely halting production to repair an asset, you don’t have to plan around any stoppages.
Unplanned downtime: When you don’t repair your assets regularly you run the risk of unexpected equipment failures that can result in costly disruptions. Much-needed equipment may be unusable until it’s been properly repaired and returned to normal working order.
Expensive repairs: If an asset is critical to your normal business operations, shutting it down to maintain it can be expensive. In addition to work stoppages, there are also costs associated with hiring technicians needed to come and perform repairs.
Budgeting difficulty: Planning your maintenance budget around big, costly asset failures when you don’t know which asset will break or when, or how long it will take to fix, is a challenge for many organizations.
Delays in finding necessary parts: Without a maintenance plan or a stockroom full of spare parts, sourcing what you need to perform a critical repair could take months. When a critical asset breaks, maintenance can be delayed until the parts needed to repair it are available.
Unsafe operating conditions: When assets go unchecked intentionally as part of a reactive or run-to-failure maintenance strategy, workers are put at risk from operating unsafe equipment.
Poor performance: Assets that aren’t repaired regularly don’t just break down all at once, they degrade in quality over days, months and even years. Assets put under continuous stress without routine maintenance are unlikely to perform at optimal levels.
High energy costs: When asset performance drops, so does asset efficiency. Assets that run longer without being maintained properly consume more energy, driving up costs as well as contributing to a greater carbon footprint.
While large businesses that depend on complex assets as part of their daily operations are largely shifting away from reactive maintenance towards more proactive, preventive and predictive strategies, there are still instances where reactive maintenance make sense—especially for smaller organizations where the initial costs of a preventive or predictive strategy is prohibitive. Here are a few examples.
Many organizations that depend on vehicles as part of their core business rely on reactive maintenance to keep them running. While they may see the value in switching to another strategy in the long run, the resources needed to start a preventive or predictive maintenance strategy may be simply out of reach. Since the assets in question (vehicles) are relatively cheap and easy to repair, it’s more cost effective for some organizations to wait until they break and fix them.
The hospitality industry deploys reactive maintenance strategies to care for many of its assets including HVACs, laundry machines, elevators, boilers and keycard systems. Like with the infrastructure example, many of these assets simply can’t be repaired until they show visible signs of failure. For example, a keycard that enables a guest to access a room is considered “working” until it can no longer function. Since repairing or replacing the keycard is both cost effective and easy for an employee to perform, a reactive maintenance approach is best.
When it comes to fixing roads, interstates, bridges, subways, railroad lines and other critical transportation infrastructure assets, most state and federal maintenance programs use a reactive maintenance approach. This is largely because normal wear and tear is hard to fix on structures until it becomes apparent after a failure has occurred. A good example of this is the lines that demarcate lanes on a roadway—they can’t be painted over until they have faded with time and use.
For organizations that own and operate more complex assets, reactive maintenance can be both costly and inefficient. A more proactive, comprehensive strategy such as preventive or predictive maintenance is required.
Preventive maintenance uses maintenance records, checklists, work orders and performance metrics to help technicians spot opportunities to perform planned maintenance on assets before they break. With capabilities like machine learning, data analytics and asset health monitoring, modern preventive maintenance programs help reduce maintenance costs, optimize maintenance activities and increase the life expectancy of assets.
Many preventive maintenance strategies rely on enterprise asset management (EAM) approaches and maintenance software such as a computerized maintenance management system (CMMS) to increase asset stability, ensure compliance, manage maintenance tasks and resolve issues that can impact production.
Predictive maintenance builds on the condition-based monitoring capabilities of preventive maintenance with real-time monitoring capabilities that allow for continuous assessment and reassessment of an asset’s condition. With a predictive maintenance approach, sensors collect data in real time that is then fed into AI-enabled EAM and CMMS software where advanced data analysis tools identify, detect and address maintenance issues as they occur.
Additionally, algorithms can be deployed to create models that will help spot potential problems in the future and address them before they cause equipment breakdown. Predictive maintenance programs have been shown to decrease asset downtime by as much as 35 to 50 percent and increase asset lifespans by 20 to 40 percent.1
Both EAM and CMMS play important roles in preventive and predictive maintenance strategies.
Enterprise asset management, or EAM, is an approach to asset performance management (APM) that combines software, systems and services to help technicians strategically maintain their assets. Today, with everything from pipelines to skyscrapers connected via the Internet of Things (IoT) advanced analytics and artificial intelligence (AI) have become increasingly important to EAM. Data gathered from sensors is analyzed in seconds with AI techniques generating insights into why equipment might not be functioning properly.
CMMS gathers critical asset information in one place where it can be of better use to maintenance technicians. The key component of CMMS is a database that organizes critical asset information along with the resources needed to support asset maintenance. CMMS software is widely used across many different industries including manufacturing, transportation, construction and energy.
Embracing preventive and predictive maintenance approaches can yield many benefits to organizations willing to make the upfront investment.
By rigorously systematizing maintenance and inspections, preventive and predictive maintenance programs help ensure assets achieve their full lifecycles.
Preventive and predictive maintenance programs increase asset uptime, improve vendor management and workflow capabilities and help organize maintenance teams so they are more productive.
Preventive and predictive maintenance allows maintenance leaders to monitor asset performance and condition in real time so they can spot opportunities to perform preventive maintenance before a critical asset fails.
Preventive and predictive maintenance allow teams to consider more than just an asset’s condition when making a decision around maintenance including factors such as resources, worker safety issues, security risks and projected downtime.
Large organizations know how much data management and storage requirements can vary from region to region. Preventive and predictive maintenance help ensure your processes are in compliance no matter where you do business.
Today’s most comprehensive asset maintenance solutions are equipped with advanced technological features like IoT, AI-enhanced analytics and monitoring and cloud-based capabilities. The IBM Maximo® Application Suite is a fully integrated platform that helps companies evolve their maintenance operations from timed scheduling to condition-based, predictive maintenance informed by real-time insights.
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