What is asset criticality analysis?

By carefully evaluating both the likelihood and consequences of failure, maintenance teams can use criticality analysis to develop targeted strategies, improve asset reliability and reduce operational risks.

Today, most successful enterprises rely on thousands of physical assets to maintain production. Increasingly, maintaining these assets requires the integration of new technologies like digital enterprise asset management (EAM) systems, condition-monitoring (CM) platforms and predictive maintenance workflows. Asset criticality analysis is essential in assessing where and how to apply these technologies as part of a modern reliability-centered maintenance strategy.

Criticality analysis serves as the foundation for many asset management initiatives, including:

• Preventive maintenance programs
• Predictive maintenance strategies
• Reliability-centered maintenance initiatives
• Failure mode and effects analysis (FMEA)

Asset criticality assessments are central to asset criticality analysis, enabling organizations to measure the value of their physical assets according to several factors:

• How likely is an asset to fail?
• If the asset fails, how significant are the consequences?
• How important is an asset to core business operations?
• How does an asset impact worker safety?
• Is an asset compliant with all relevant regulations?
• How well does an asset perform from a total cost of ownership (TCO) perspective?

The purpose of an asset criticality assessment is to produce a criticality rating or criticality score so maintenance managers can compare it to other assets. Without a criticality assessment, an organization can’t perform asset criticality analysis.

Asset criticality and asset condition are often confused, and while the two terms are related, there are several important differences worth noting. When the terms are misapplied, organizations risk optimizing their maintenance processes for the wrong thing.

While asset condition describes the current health or operating state of an asset, asset criticality measures the importance of the asset to an organization. For example, an aging pump with excessive vibration might be accurately described as being in poor condition. However, unless the pump is key to producing goods and services, it is unlikely to be considered critical.

Unlike asset condition, asset criticality considers the role the pump plays in operations, productivity and the financial impact of its failure on the company.

Maintenance teams perform asset criticality analysis by following a seven-step process to identify, evaluate and rank assets according to risk of failure and potential impact of failure on core business processes:

1. Create an asset list
2. Define evaluation criteria
3. Assess the likelihood of failure
4. Evaluate the consequences of failure
5. Apply a scoring system
6. Assign asset criticality rankings
7. Integrate findings into maintenance programs

Here’s a closer look at each step.

The first step of asset criticality analysis is creating a complete list of all physical assets that an organization owns, from production equipment and facilities infrastructure to electrical systems, components and instrumentation.

To streamline this process, modern organizations often rely on a computerized maintenance management system (CMMS). A CMMS is software that uses artificial intelligence (AI), machine learning (ML) and Internet of Things (IoT) technology to maintain work orders, maintenance histories and other records that are essential to asset criticality analysis.

Step 2 requires that organizations establish criteria to measure asset criticality. Common considerations during this stage include worker safety, impact on productivity and operations, environmental and financial impact and regulatory compliance.

Maintenance managers should be able to accurately assess each asset in the list from Step 1 according to the criteria laid out in Step 2.

The next step in asset criticality analysis is evaluating the likelihood of failure for each asset. For example, to determine the likelihood of failure for a conveyor belt in a manufacturing plant, maintenance planners would consider its age, wear-and-tear, projected useful and maintenance conditions, along with other factors.

Advanced organizations increasingly incorporate predictive maintenance technologies like IoT sensors, vibration analysis and machine learning algorithms for more accurate failure probabilities.

The fourth step is arguably the most important in asset criticality analysis. While Step 3 tells an organization when an asset is likely to fail, Step 4 maps out how a failure would likely impact business operations.

While two different components might have the same failure probability, if one supports a critical process and the other doesn’t, it will receive a higher criticality rating. This change can happen even though it might be less expensive and less complex.

Scoring systems help maintenance planners convert subjective judgments about asset importance into objective, numerical ratings.

While there is no universal standard for scoring systems, most organizations use a risk-based method that combines the likelihood of failure with the consequences of failure on a 1–5 or 1–10 scale. For this scale, 1 represents a lower risk and consequence and 10 represents a higher one. The goal is not to produce a mathematically perfect score but to create a consistent methodology that can be used for every physical asset in a portfolio.

After an organization has established its scoring system, it ranks its assets according to criticality. Asset criticality rankings help organizations answer important questions about how to best maintain their assets. These questions could be: 

• Which assets require regularly planned visual inspections and which require technicians to monitor them using a real-time condition-monitoring platform?
• Which assets justify larger investments in predictive maintenance technologies versus which assets can be safely maintained on a manual, reactive plan?
• Which assets require redundancy?
• Which assets should receive priority status during maintenance planning?

The final step of asset criticality analysis involves integrating new insights and best practices discovered during the first six steps into existing maintenance programs.

Modern organizations use criticality rankings to determine several actions, including preventive maintenance activities, work order prioritization, resource allocation and capital planning.

As part of asset criticality analysis, modern organizations are also increasingly turning to structured risk assessment methodologies to help them better identify, evaluate and prioritize risk around critical assets. Failure mode and effects analysis (FMEA) and reliability-centered maintenance (RCM) are two of the most effective:

• FMEA examines potential failure modes and their operational impact on an organization, helping maintenance teams identify ways to prevent failure or at least mitigate its impact.
• RCM builds on information generated by FMEA to help teams develop optimized maintenance strategies that can increase equipment reliability by aligning maintenance activities with failure characteristics. Together, these frameworks provide a structured approach to improving asset reliability while minimizing unnecessary maintenance.

Asset criticality analysis is a vital tool for helping enterprises identify the assets that are most important to their core business processes and prioritize maintenance accordingly.

Here’s a look at some of its strongest benefits.

Strong, well-informed maintenance planning ensures that organizations get the most out of their assets throughout their entire lifecycles, from planning through installation, operation and retirement. Rather than applying the same maintenance schedules to every asset, asset criticality analysis helps teams tailor individual approaches to meet the demands of failure risk and criticality.

For example, while a critical production compressor might require monthly inspections, a noncritical warehouse ventilation fan might only need to be tested once a quarter. Maintaining both these assets on the same maintenance plan would be expensive and ineffective.

Maintenance resources are finite, and maintenance planners must constantly create and adjust strategies to fit budgeting needs, operational compliance requirements and workers’ schedules. Asset criticality analysis helps them better direct personnel and parts toward assets that are critical to generating business value and maximizing ROI.

For example, in an automotive manufacturing plant, 25 technicians are responsible for maintaining over 2,000 production assets. Their manager knows that they only have enough staff to complete 30 preventive maintenance tasks per week, even though 50 are due according to the work orders generated by a CMMS. Criticality analysis helps the team prioritize tasks to ensure that productivity isn’t interrupted and the most important assets are fixed first.

Unexpected failures often disrupt operations and generate substantial costs. According to a recent report that focused on the manufacturing industry, unplanned downtime costs roughly USD 50 billion dollars annually—USD 260,000 per hour, or almost USD 9,000 dollars per minute.

By helping maintenance managers identify critical assets and focus preventive maintenance efforts on their most high-risk equipment, criticality analysis helps reduce unplanned downtime and improve operational continuity.

Predictive maintenance technologies help organizations use operational data and real-time condition-monitoring to predict when assets are likely to fail. But they are expensive, often requiring significant upfront investments in sensors, analytics platforms and data infrastructure.

Asset criticality analysis helps organizations determine where these investments will deliver the most value. It also helps professionals realize where they can afford to continue to monitor assets with less expensive techniques like routine maintenance and visual inspections.

Maintenance strategies informed by asset criticality assessments enable technicians to address equipment vulnerabilities before they result in failures. By prioritizing maintenance activities more strategically, they can reduce the number of breakdowns and improve asset reliability over time.

As reliability improves, organizations also extend asset lifecycles, increase the stability of production processes and reduce overall maintenance costs.

Healthier and more reliable assets are typically higher-performing assets. As maintenance teams apply criticality analysis across the entire asset lifecycle, they often see an uptick in asset performance, as well.

By ensuring maintenance activities concentrate on equipment with the highest criticality—not just equipment that breaks down most often—maintenance managers ensure that their most valuable assets are always performing at peak levels.

Asset criticality analysis originated in industrial maintenance programs but has spread to most sectors. Today, it helps organizations develop maintenance strategies for assets as diverse as manufacturing plants, oil and gas facilities and healthcare systems.

Here are five use cases for asset criticality analysis by industry.

The manufacturing industry relies on asset criticality analysis to identify the assets in their production lines whose failure would most impact production.

By assigning criticality levels and forming an asset hierarchy, these organizations can decide which pieces of equipment to run on complex, expensive proactive maintenance plans versus less expensive, less complicated, reactive ones.

Critical assets in the manufacturing industry typically include:

• Production lines
• Compressors
• Boilers
• Industrial robots
• Packaging systems

The oil and gas industry relies on large, complex assets for most of its core business processes, including drilling for, refining and transporting large amounts of oil and natural gas. In an industry where an hour of unplanned downtime can cost as much as USD 500,000, ensuring critical assets are well maintained is an undeniable priority.

Failure of large assets like oil rigs, pipelines and refinery equipment can cause dangerous conditions quickly. To ensure asset health, oil and gas companies use equipment criticality assessments and analysis to determine which assets pose the greatest risk to operations and workers plan maintenance activities accordingly.

Utilities companies must operate large, interconnected networks of assets as part of their core business processes. Interruptions can be devastating, causing power outages and environmental hazards as well as financial penalties for violating regulations.

Criticality assessments help utilities operators improve equipment reliability and reduce service interruptions for large areas. These are some examples of critical assets in utilities infrastructure:

• Turbines
• Transformers
• Generators
• Circuit breakers
• Substations

Hospitals and other types of medical facilities depend on large, complex assets to improve patient health and maintain the comfort and safety of doctors, clinical workers and technicians in large, interconnected facilities.

Asset criticality analysis helps healthcare organizations prioritize a diverse set of maintenance needs to ensure operational continuity and ensure the safety of patients. Here are some critical assets in the healthcare sector:

• Medical imaging equipment
• Ventilation systems
• Backup generators
• Sterilization equipment
• Laboratory systems