Introduction to criticality analysis
Manufacturers with a mandate to reduce downtime on the factory floor and improve their operational efficiency find it best to employ criticality analysis to help them prioritize maintenance tasks. They view maintenance holistically in terms of addressing risk, costs and impact on their operations.
By improving maintenance efficiency, you lower the total cost of ownership of equipment. You can also avoid sudden malfunctions or outright equipment failures that require repairs or replacement.
What is criticality analysis?
Criticality analysis is a method used to evaluate the importance of equipment based on its role in production, failure likelihood and the impact of its failure.
The purpose of initiating asset criticality analysis is to help identify which assets are most critical to operations, ensuring maintenance resources are focused on minimizing potential downtime and disruptions. As you gather information, such as through sensor data collection in the factory, you will be on pace to become a data-driven manufacturing company.
How criticality analysis is conducted
There are three main components to conducting criticality analysis:
Data collection: It’s important to engage in comprehensive machine data collection to get precise information about how equipment is performing in your factory. You can get a treasure trove of data from sources such as sensors and programmable logic controllers (PLCs). Data about current draw, oil condition, vibration, temperature and other factors provides insight into equipment failure rates. Such details will also help you assess each device’s operational importance.
Failure modes and effects analysis (FMEA): Manufacturers often use FMEA to identify potential failure modes as they rank their equipment according to the potential severity of failure. There are two main types of FMEA: Design Failure Mode and Effects Analysis (DFMEA) and Process Failure Mode and Effects Analysis (PFMEA).
With DFMEA, you focus on the product design process. Typically used for analyzing consumer product manufacturing, you can also apply DFMEA to an entire production line’s manufacturing machinery. The goal is to determine potential failure points in equipment and estimate the probability of these failures. Then, rank the factors or events according to an RPN or risk priority number based on scoring probability, impact and detection difficulty.
Design FMEA helps you modify and improve current design after identifying weaknesses, before taking a product into prototyping and testing.
When analyzing manufacturing processes, you use PFMEA, which assesses how likely a particular failure event might be and its impact on your factory operations. The PFMEA data helps you determine which equipment to prioritize for maintenance services and repairs. If a piece of vital equipment has a relatively low risk of breaking down but whose failure would cause severe disruptions, you will rank this device with high priority for preventative maintenance.
Risk matrix: Savvy manufacturers create a risk matrix, also called a criticality matrix, to help them see the likelihood of equipment failures and assess their impact on production, customers, worker safety and the environment.
How to create a criticality matrix
Step 1: Define criteria
List relevant factors such as operational impact, cost of failure, safety risks and failure frequency. The goal here is to identify levels of criticality based on all the available data you can gather in your manufacturing facility, including insights from your in-house equipment experts.
Which machines should you rank as a high priority for preventative maintenance? You’ll determine this by conducting root cause failure analysis (RCFA).
The RCFA process typically begins with an identifiable problem in the form of a triggering incident, such as flaws you find in finished products or malfunctioning equipment.
Identify and document the problems or equipment symptoms with hard data, such as to note a finished product is out of specification by a specific amount. In RCFA, list potential causes for the problem identified in the triggering incident, using all gathered data to narrow down the most likely reason for failure.
Step 2: Assign scores
During the criticality assessment, you will score each factor on a scale (such as 1-5) to reflect severity, likelihood and overall risk. Examine factors such as the mean time between failures or MTBF and the history of corrective maintenance while taking into account the lead time necessary for obtaining spare parts.
Step 3: Plot the matrix
Create a matrix with “Likelihood” on one axis and “Impact” on the other. Categorize equipment based on its position in the matrix. Then, you can see at a glance what machines and devices deserve the highest priority for maintenance, which is essential for avoiding disruptions from breakdowns.
Step 4: Prioritize assets
Use the criticality matrix to prioritize maintenance on high-risk equipment and ensure that critical assets receive appropriate attention according to the criticality levels you’ve assessed.
Steps to implement criticality analysis
Step 1: Identify assets
To get started with industrial asset management, outline all equipment and their roles within the production process.
Step 2: Rank criticality
Use FMEA and risk matrices to rank equipment based on its failure impact and likelihood. Your team will assign a rating to each asset according to the severity of failure. For example, a conveyor system failure could rank as “5” for operations but only a “1” in terms of potential environmental harm.
Step 3: Implement prioritized maintenance
Develop maintenance schedules prioritizing the highest-risk equipment as revealed in your machine risk assessment.
Benefits of criticality analysis in industrial maintenance
Conducting a criticality analysis confers many benefits to improve your industrial maintenance processes, including:
- Correctly prioritizing maintenance efforts: Criticality analysis helps determine where to allocate maintenance resources most effectively, focusing on equipment with the highest risk.
- Drives effective preventive and predictive maintenance programs: Knowing the criticality of an asset will help you take care of the most important items first, instead of going by instinct or general “rules of thumb”.
- Reducing unplanned downtime: By targeting critical equipment, companies can prevent unexpected breakdowns, leading to fewer interruptions in production. This is especially crucial amid supply chain disruptions, which could delay you receiving replacement equipment or parts.
- Cost savings: Targeting critical assets reduces reactive maintenance, enabling better budget allocation and overall operational efficiency.
Assess your current maintenance strategies
As you and your fellow stakeholders recognize the importance of criticality analysis in industrial maintenance to help avoid unplanned downtime, you’ll want to begin assessing your current maintenance strategies by conducting an asset criticality assessment with details spelled out in the criticality matrix.
Understanding asset criticality is crucial for fine-tuning your industrial maintenance operations. Doing so will improve equipment uptime and efficiency. To learn more, contact us today.
