The resources available for machine maintenance and asset management of an organization are limited: money, labor availability and time, for instance. Therefore, it is necessary to prioritize and concentrate efforts in order to increase machine reliability effectively.
In this sense, criticality is the attribute that demonstrates the importance of a machine within a productive process, that is, how much a given machine is indispensable in the context of an operational system. Based on asset criticality, it is possible to define the prioritization of maintenance actions, in order to ensure that the production system works as close to its nominal capacity as possible.
How to determine the criticality of a machine
There is, of course, a general idea especially among more experienced collaborators of which are the most critical machines within a given production process. However, professionals from different sectors, with different views and experiences, may disagree on machine criticality ranking.
For example, if the question is directed to a professional part of the maintenance team, the answer is likely to be the equipment whose maintenance is more time consuming and harder to perform or whose maintenance interventions are more frequent. If the question is asked to the plant operation responsible, the answer may be different: perhaps the production bottleneck machine or the one with greatest production capacity. The responses from Quality or Health and Safety departments will probably be different as well, and thus, a great variability in the definition process will take place.
Therefore, this “intuition” is usually not sufficient to ensure an objective decision, since the definition of criticality is complex and can involve several variables and departments.
To help with this task, there are more structured methods, such as the ABC method for asset criticality. This method makes use of a machine classification system in terms of severity of failure occurrence. Six criteria are taken into account:
- Safety: Dangerous machines, such as presses and guillotines, can cause serious damage to the health of the operator.
- Product quality: Some machines carry out high precision processes and, in this way, the lowest level of misalignment can result in loss of quality of the manufactured product.
- Impact on production: Failures in production process bottleneck machines can have a strong impact on productivity to the plant. In some cases, they can even lead to total production stops. Therefore, this is an extremely important criterion in criticality analysis.
- Mean Time Between Failures (MTBF): This criterion deals with the time elapsed between failures in a machine.
- Mean Time to Recovery (MTTR): This criterion represents the average time required to replace or repair a faulty component, or even to restart the machine.
- Maintenance Costs: Money to be spent on repairing a specific machine that may fail. This expense varies according to the failure, but in general, it’s possible to infer if the asset requires high expenses with spare parts and so on. For example, if the asset is sourced overseas, the cost of replacing defective parts may be higher.
Each of the analyzed machines must be classified in the six criteria mentioned above, according to three levels of impact:
- A: high impact;
- B: medium impact;
- C: no impact.
After performing this analysis machine by machine, criterion by criterion (1 to 6), the decision flow chart shall be used:
By this method, the machines will be classified as follows:
- A: Highly critical equipment.
- B: Moderately critical equipment.
- C: Equipment of low criticality in the process.
In addition to the ABC, there are several other methods of evaluating the criticality of machines, such as GUT matrix, Reliability Centred Maintenance (RCM) and Failure Mode and Effect Analysis (FMEA). These and other methods will be covered in future texts on the blog.
The critical machines have been defined. And now, whats is the next step?
Once the organization has defined which assets are the most critical, it’s time to take action. A good way to start is by structuring a maintenance plan that involves the different maintenance strategies: corrective (run to failure), preventive and predictive.
Critical machines should be the focus of predictive maintenance because it is intended to identify potential failures, preferently at an early stage, to prevent further damage to the machine. In this sense, vibration analysis is a highly efficient technique to increase the availability of these vital assets to the production system.
Looking to provide a quality solution for this technique, Dynamox has developed a device, accompanied by Mobile Application and a Web Platform, whose function is to monitor the vibration and temperature of the machinery and its components. Through DynaPredict you can, via wireless Bluetooth connection, access historical data, perform spectral analysis and know for a fact, the condition and health of your assets.