Reactive, preventive or predictive?
When it comes to maintenance, which is the right solution for a plant?
Every day, management and maintenance teams are either being praised or blamed because of decisions they made with regard to maintenance strategies used in a plant.
Reactive maintenance can provide low operational costs. Yet in the worst case, this strategy can also wipe out any cost efficiency if a plant’s uptime is jeopardized. Predictive maintenance requires a completely different operational culture. It can even be easily neglected, although this strategy may provide the best plant availability.
By understanding the benefits and weaknesses of each of the three types of maintenance strategies, it is possible to make the right decision of which to use in every case. In fact, especially for new projects, it is possible to use a combination of all three strategies to cover even on/off valves without any considerable extra costs.
Reactive maintenance is essentially letting something run until it breaks. This means that no effort or action is taken to maintain the equipment. This was the most predominant maintenance mode in the US as late as 2000.
Preventive maintenance is carried out according to the calendar year. This is a good approach for standard replaceable components that wear out with use.
Predictive maintenance takes advantage of diagnostics information to help make a better maintenance plan. Diagnostic-based maintenance generally shortens repair time and extends the useful life of the asset.
Introducing Reliability Centered Maintenance – RCM
RCM recognizes that not all equipment within a plant is of equal importance to the process or its safety. Therefore, the assets are classified based on their criticality and the maintenance strategy is selected accordingly. RCM suggests that less than 10% should be allocated to reactive maintenance, 25–35% to preventive maintenance and 45–55% to predictive maintenance. When comparing the different strategies, management may not readily understand the savings potential due to startup costs.
Still, it’s important to remember that predictive and RCM can be enabled easily when the assets are intelligent. The steps are simple. Select assets capable of analyzing and storing performance information during the normal plant run time. Analyze performance in the real operating conditions. No extra work is needed to carry out tests – just simply analyze the results.
- In predictive and RCM maintenance strategies saving potential is not readily seen by management due to startup costs
- Predictive and RCM can be enabled easily when selecting assets to be intelligent
Case: Refinery maintenance planning
Using predictive maintenance for critical emergency shutdown valves in a Brasilian refinery resulted the following outcome. A total of 23 ESD valves were analyzed based on diagnostics. All of them were then taken into the maintenance workshop.
Fourteen proved to be fine; 9 valves were fully maintained. As a result, the customer reduced maintenance costs by 58% and maintenance shutdown time was exactly according to schedule.
Reach a higher-level maintenance strategy
By using a combination of different maintenance strategies within a plant depending on an asset’s criticality, it is possible to reach a higher-level maintenance strategy. Predictive and RCM strategies utilize diagnostics information to bring more cost efficiency to the maintenance organization and optimized availability to plant operation.
End users and EPCs alike can gain better maintenance results when they take advantage of smart digital technology with asset operation as well as with plant startup. If investment in the beginning of the green field project is too high there is easy way to enable such capabilities for the future. End user should indicate used maintenance strategy in the specification and latest in purchase order to EPC. This would guide EPC directly to enable purchased green field plant to have technology fitted into the needed purpose. Information which is utilized in predictive maintenance or RCM maintenance strategies can be generated in the assets itself with very cost efficient method. Later on it’s upon end user if they are willing utilizing this data with asset management software. Investment to make assets like process industry valves to be as a smart is not big but impact on cost savings is huge. For this reason we are encouraging to utilize this technology on assets as much as possible.
Simply making specifications e.g. such way that every automated valve on the field is capable to analyze and locally store performance related analysis information will make huge impact for the end user. On cost wise it doesn’t include any additional costs and it doesn’t yet necessarily include any asset management software investments.
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