In our previous article about maintenance, we described the strategies one can adopt to monitor assets in their plant. We also discussed Predictive Maintenance, which can help schedule maintenance procedures and allow for better asset optimization. Predictive Maintenance can have many advantages for a firm, such as increased efficiency of the entire production process, savings, and even reduced environmental impact. However, it can also have its drawbacks. Implementing Predictive Maintenance can be very expensive and time-consuming, and replacing an existing maintenance strategy could have a ripple effect that necessitates change in other areas of an organization. This means that efforts by Heads of Production, Heads of Maintenance and CIOs to implement Predictive Maintenance could be met with a good deal of pushback.

If this is the case, it is best to acknowledge that Predictive Maintenance is not actually the panacea for all things maintenance and that you will not necessarily need to make sweeping changes to the rest of the plant. Contrarily, there are a few steps one can take to identify the positive results different maintenance strategies can have on one’s organization.

One way to begin is to identify the assets in your plant that would really benefit from a maintenance strategy change and figure out to what degree these assets would benefit. The most common way to do this is to conduct a Criticality of Equipment Analysis. By ranking your assets according to their criticality, this methodology can help create a roadmap for implementing a new maintenance strategy.

Criticality of Equipment: What Is It?

The idea behind the Criticality of Equipment approach is to conduct an analysis of the plant’s assets in order to better understand to what degree the risks related to each asset can impact your operation. It is very difficult to conduct this type of assessment as there is no real standardized process for doing so. This is largely because risk always refers to an event and not to an item, meaning the difficult part of the calculation is moving from an analysis of the impact of risky events that might be caused by the equipment to a general assessment of the equipment itself. To overcome this, one can either follow their company’s risk matrices or the Failure Mode Effects and Criticality Analysis (FMECA) method, which aims to determine causes and effects of failures in the design stage of a manufacturing process.

Method 1: An Intuitive Approach to Criticality of Equipment

The first step in conducting the Criticality of Equipment analysis is to gather people from different departments of your company and agree on the risk matrices. Introducing different perspectives into the conversion can greatly contribute to the general understanding of the issue and can help prioritize risks. For example: a failure with an impact that seems mild from a corporate perspective, might be severe from an engineering perspective.

As we mentioned before, because risk only refers to events, when it comes to equipment, the risky events are considered failures. The problem is that equipment can fail in many different ways and, in order to not overcomplicate the analysis, some experts suggest only considering one event for each piece of equipment: the Maximum Reasonable Outcome (MRO). The MRO is an event that is likely to occur and of which the impact would be very negative. This exemplifies why this analysis should be conducted on a company-wide basis and why it is so important to agree on the risk matrices beforehand. Because there are so many different types of risk to consider—the most important being health, safety, environment and production loss—experts suggest only considering the type that would have the most negative impact.

The result of this process, which allows the failure to be more thoughtfully considered and, therefore, ranked amongst the plant’s assets, should be a Risk Priority Number (RPN). When only considering one type of risk, the most common approach for teasing out the RPN is to use a 6x6 matrix that plots the probability of the failure to happen as a function of the y-axis and the severity of the consequence of the failure as a function of the x-axis. 1 would represent a failure that is unlikely to occur and that has no impact, while 36 would be an event that is very likely to occur and that would have severe consequences (see Image 1).

Image 1: The Risk Matrix

Carrying out this process for each piece of equipment makes it possible to cluster the RPNs into different groups and assemble a ranking of the plant’s assets according to their criticality.

Method 2: The FME(C)A Approach

Another way to approach the Criticality of Equipment analysis is to use the Failure Modes and Effects Analysis. This methodology was developed in the 1940s by the US military, and, by the 1960s, was already in use across many different industries. This methodology’s aim is not to help determine how critical an asset is from different perspectives, but rather to see how and why an asset can fail, and how the consequences of that failure could be mitigated.

The FMECA also includes a criticality analysis that calculates the probability of the failure to occur, as well as the severity of the failure, while also taking the dormancy time into account. Dormancy time is related to the variable of Detection, which indicates how likely the failure is to be detected. It is always rated on a 1 to 6 scale, with 1 being a very high probability of detection, and a 6 being a very low probability of detection.

The FMECA generally requires many resources and is much more time-consuming than the preceding methodology. While some of its outcomes, such as the inclusion of the RPN, are the same, the amount of detail with which each analysis can be conducted varies greatly. Other variables that can be added include, but are not limited to, redundancy, utilization, and age of the asset. The primary outcome of the analysis, however, is a clear set of recommendations on how to mitigate failures.

Download the free PDF of the AiSight's Criticality of Equipment Worksheet

Criticality of Equipment: Your Compass to Maintenance Strategies

Both of the previously mentioned methodologies are valid and can serve as your compass to choosing the right maintenance strategy for each piece of your company’s equipment. Performing the Criticality of Equipment analysis can help you better determine the number of spare parts you can hold in your inventory, help you prioritize future upgrades and replacements, and, most importantly, provide you with a clear overview of the maintenance strategy you should adopt for each piece of equipment.

Implementing advanced reliability efforts can be very expensive and time-consuming. This makes calculations such as the ROI and the Criticality of Equipment fundamental. If an asset has a very high score, it means that failures arising from that asset will negatively impact your plant. In such cases, constantly monitoring that item can improve its efficiency and help you prevent unplanned stoppages of production. For a non-critical item, a Reactive Maintenance approach might still be sufficient (check out all of the maintenance strategies you can choose).

Though Predictive Maintenance has traditionally required a great deal of time and money to implement, the AiSight Sensor kit has made it easier and cheaper than ever to keep your equipment up and running. It is as simple as renting our sensors and paying a small monthly fee for the advanced analytics they provide. Installing the AiSight sensor only takes 5 minutes, while calibrating the software to your machine only takes a few hours. Once the sensors are set up, you will be able to make reliability improvements on all of your machines, without having to pick and choose what to prioritize. If you would like to know which machines are compatible with our solution, click here.