Guide to Corrective Maintenance For Industrial Assets 

Industrial assets are not immune to Murphy’s law: Even the most reliable equipment can fail at any time. Every year over 636 pipeline incidents and 8.3 failures per wind turbine occur.

Corrective maintenance (CM) is the antidote to this vicious cycle. Timely assessments and early intervention reduce the risks of complete failures and prolonged downtime. On the other hand, companies that exclude corrective measures from maintenance contracts could face 30% more unexpected costs.

Learn about the key principles of effective corrective maintenance strategies and how to optimize your processes with emerging technologies.

What is Corrective Maintenance?

Corrective maintenance involves the identification, repair, or replacement of faulty assets to proper operating conditions to avoid damage exacerbation and minimize downtime. It’s a standard approach for most organizations, accounting for up to 60% of all operation and maintenance (O&M) activities.

Corrective maintenance is usually initiated when:

• Visual signs of damage or distress are apparent
• A routine inspection reveals potential damage
• An asset monitoring system highlights an issue

For instance, lighting protection system testing revealed faulty conductors — the system must then be replaced. A drone cell tower inspection detected thinning of protective coatings on pylons — the team plans for a new paint job.

Corrective vs Reactive Maintenance

The terms corrective and reactive maintenance are often used interchangeably. Although that isn’t fully accurate. Reactive maintenance is always unplanned and concerns unexpected asset breakdowns that halt operations and require all hands on deck ASAP.

Corrective maintenance, in turn, concerns assets in an operational state, but showing early signs of malfunction. Therefore, CM can be planned, unplanned, and even postponed if the issue isn’t critical to safety or compliance.

Corrective vs Preventive Maintenance

Corrective maintenance deals with issues as they emerge. Preventive maintenance (PM) aims to reduce the odds of failures to the lowest minimum.

The first distinction between corrective and preventive maintenance is their purpose. Preventive maintenance assumes regular asset health monitoring, proactive issue resolution, and root cause analysis. In contrast, CM prioritizes the resolution of immediate problems with an aim to quickly restore operations.

Preventive and corrective maintenance also have different levels of planning. Predictive maintenance requires regular inspections and servicing at predetermined intervals. On the process side, this involves more coordination between different teams to ensure timely part ordering, technician dispatches, and optimized shutdown schedules.

With CM, you focus less on beforehand planning and more on present-day problems. Issues are handled based on determined priority scores, with some being deferred until the next planned shutdown.

Cost is the final difference. Since predictive maintenance assumes frequent inspections and continuous monitoring, you invest more upfront. However, you save more by addressing issues at the early stage, which means less downtime and a longer asset service life. With CM, it’s vice versa: you spend less on initial maintenance but might deal with larger repairs and unforeseen breakdowns later.

Types of Corrective Maintenance

Different types of corrective maintenance strategies are applied, depending on the defect severity, incident impact, and criticality of an asset or its components.

Emergency corrective maintenance occurs when a significant failure can disrupt other components/assets or significantly harm technicians, local residents, or the environment at large. Depending on the damage, it can mean immediate repair, isolation of a damaged asset, or a complete overhaul. For example, following a recent pipeline fire, Energy Transfer had to start repairs immediately to restore power supply to thousands of affected homes and businesses in the vicinity.

Immediate corrective maintenance happens as soon as a failure occurs to minimize downtimes and prevent ancillary impacts. It may also be a necessary part of regulatory compliance. For instance, Enbridge received an amended corrective action order from the government after its ruptured pipeline released about 66M cubic feet of natural gas. The maintenance included shutdowns of hard spots, aerial and on-ground leakage inspections.

Deferred corrective maintenance covers the management of low-impact defects, where repairs can be delayed until a scheduled site shutdown. Similarly, the run-to-failure approach postpones repairs and replacements until the definitive failure. Such an approach works best for non-critical components/equipment that are easy to swap out.

Lastly, conditional corrective maintenance is the type that comes closest to preventive practices. Conditional maintenance is done when a condition monitoring system or inspection teams detect early signs of degradation or performance losses. This type of maintenance can also be delayed in time if immediate problem resolution is not feasible. For instance, flare stacks must be first sufficiently cooled down before any repairs can begin, which often requires preliminary coordination to minimize operational impacts.

Advantages of Corrective Maintenance

Corrective maintenance offers several undeniable advantages:

• Focus on immediate results: Corrective maintenance focuses on critical problems that directly impact your operations, deferring root cause analysis to a later date. In complex assets, emergency fixes can be done in a matter of days, while root cause investigation takes months. CM provides extra time for O&M managers to decide on the next best action.

• Cost-effectiveness for non-critical assets. Cosmetic repairs, component replacements, and other minor “touch-ups” are easier and cheaper to execute than major structural repairs. For non-critical equipment, these may suffice to ensure proper operations until the next replacement cycle.

• Predictable downtimes. Planned corrective maintenance is scheduled during planned shutdown slots and/or off-peak hours with minimal impacts on operational efficiencies. This approach also allows for better resource allocation as some tasks can be deferred to the next planned downtime slot.

• Extended asset lifetime: Corrective maintenance can extend the asset’s lifespan if you repair and replace faulty components right after finding issues. For example, having identified a loss of coating, it’s easier and cheaper to reapply the paint than to deal with corrosion later on.

Yet, there’s also no denying that corrective maintenance has some drawbacks. Corrective maintenance strategies don’t provide any operational foresight into asset degradation or performance loss.

Also, since some corrective actions are non-critical, some companies may skimp on those in favor of other priorities. Although that’s not the best strategy. PG&E’s case is a cautionary tale: the company faces an $800K fine for continually postponing repairs of 170,000 power lines

3 Ways to Optimize Your Corrective Maintenance Strategy

A growing backlog of corrective maintenance tasks eventually snowballs into unplanned, reactive repairs, dramatically augmenting the costs and operational impacts. New technologies can help avoid such scenarios.

Companies that digitize and automate some of the O&M processes gain 20-30% cost reduction and experience significant productivity gains. Inspection drones, IoT devices, and machine learning systems, in particular, are helping asset managers improve their asset maintenance strategies.

Streamline NDT Testing with Inspection Drones

Non-destructive testing (NDT) provides valuable data about asset health. However, it’s also a complex, time-consuming process, requiring lifting equipment, surface preparation, and manual measurements. To inspect large industrial assets like storage tanks, silos, or above-ground piping, lifting equipment or scaffolding construction may be required, leading to lengthy asset shutdowns.

Specialized NDT drones like Voliro T are changing the processes. Designed for contact work at heights, Voliro’s technology reduces NDT inspection times by 2X and saves asset owners six figures in operational expenditure with a single flight.

We’ve developed the following specialized drone payloads:

• Ultrasonic transducer. Collect thickness measurements at a range of 2-150 mm / 0.08-5.9 inches to detect early signs of surface degradation, leading to cracking, corrosion, and leaks.

• High-temperature UT. Run live A-scans on surfaces heated up to 260 °C/500 °F to gain reliable thickness measurements.

• Electromagnetic acoustic transducer (EMAT) for performing inspections of rough, dirty, and coated surfaces without any couplant application.

• Pulsed eddy-current probe for detecting early signs of corrosion under up to 100 mm of insulation.

• Dry film thickness measurement gauge to ensure proper application of protective coatings and first signs of thinning, leading to corrosion.

Thanks to advanced navigation sensors, the Voliro inspection drone can be safely flown next to high-EMI objects and in GPS-denied environments. With our technology, inspection crews have already saved over $165K on stack inspection and reduced chemical plant inspection time by 3X while also benefiting from richer asset data.

Use IoT Sensors to Collect Data Automatically

Over the past decade, sensor costs have declined by 70%, making IoT-based asset monitoring more affordable. IoT-powered systems collect real-time data and evaluate asset performance against pre-defined parameters. Should any hiccup occur — operating temperatures rise, moisture levels increase, or energy consumption elevates — your team will be alerted.

A group of Finnish researchers recently proposed an IoT platform for advanced structural health monitoring, powered by ultrasonic-guided waves (UGW) sensors. Placed to form optimal helical propagation paths, the system can locate deep internal defects and take precise thickness measurements (e.g., of pipeline walls) automatically.

Another group of US civil engineers deployed an IoT-based structural health monitoring for a cable-stayed bridge in Delaware. Powered by 120 sensors, placed throughout the bridge, the system provides a continuous supply of up-to-date data on the bridge condition and can be used to schedule diagnostic load tests.

Remote condition monitoring reduces the need for on-site inspections. Such systems also help build more accurate historical profiles of each asset to monitor degradation over time and apply corrective strategies at optimal periods.

Leverage Machine Learning For Data Processing

The flip side of greater data availability from asset management systems, drones, and IoT platforms, is the need for better analytics processes. Traditional reporting software may not be compatible with all data formats, leading to tool sprawl and data silos. To consolidate analytics and gain deeper insights, leaders are employing machine learning algorithms.

Machine learning models can analyze both structured and unstructured data, detecting anomalies faster than any trained engineer. This allows teams to apply corrective actions at the defect onset, minimizing the costs and disruptions to processes. Trained on historical data, ML models can discover a correlation chain, leading up to equipment failure, speeding up root cause analysis, and providing new insights for optimizing your maintenance strategies.

ABB, for instance, deployed ML algorithms to automate failure diagnosis and prediction in rotating machinery. As part of a 30-month study, the company installed inexpensive IoT sensors at the customer’s facilities to collect vibration data, which, according to ABB, can help detect blade issues, flow turbulence, cavities, loose parts, and misaligned components. A machine-learning model was then trained to predict the future health status of the assets.Since then, ABB scaled its remote monitoring and predictive maintenance capabilities to cover remote on-shore well pads, powertrains, and a wide range of other systems.

Conclusion

Effective corrective maintenance is a bedrock practice of asset management. Not all failure types can be anticipated or predicted even with state-of-the-art technology. What can (and should be!) changed, however, in the process efficiency.

Thanks to inspection drones like Voliro, teams can inspect hard-to-reach areas (such as angled sections of the pipeline) without rope access. With a high-temp UT probe, you can also locate defects on assets in use like flare stacks and shafts, further reducing downtime. The best part? You don’t have to worry about drone maintenance as our subscription coverscertification, repairs, and replacements.