What is maintenance and why is it important? 

Maintenance is all about ensuring an asset’s intended function. It is the combination of technical, supervisory and administrative activities that are aimed at maintaining or restoring an item to a state where it can carry out this function. Maintenance is vital for achieving a good return on investment.

Achieving optimal maintenance requires balancing the costs of executing maintenance and the benefits achieved by those maintenance efforts. It is that balance we constantly seek to optimize by use of Asset Integrity Hub – both for corrective, preventive and predictive measures.

Maintenance strategies  

Maintenance strategies are plans or approaches used to manage maintenance activities and ensure that equipment and assets are functioning optimally. There are two basic categories of maintenance strategies that are implemented to:

• correct an item after it has failed (corrective maintenance) 

• prevent an item from failing (preventive maintenance)

In other words, after a failure is identified, corrective maintenance is carried out (reactively). If the failure is predicted, preventive maintenance is carried out before the failure can occur (proactively). 

Corrective maintenance refers to repairing or maintaining components only when they fail, usually in an emergency situation, and is therefore more expensive than preventive maintenance. In the case of offshore wind turbines, the limited weather windows create access restrictions that make corrective maintenance particularly costly.  

Preventive maintenance can be done through predetermined/scheduled or condition-based methods. It is described as maintenance performed at predetermined intervals or according to specific criteria to decrease the likelihood of equipment failure or degradation in performance. There are typically three objectives for carrying out preventive maintenance tasks:  

• to prevent a potential failure 
• to identify the beginning of a failure 
• or to uncover a concealed failure 

Predetermined maintenance involves scheduling maintenance actions in advance, which is suitable when the lifetime of the component is known with a high level of certainty.  

Preventive maintenance can further be classified into rule-based, reliability-based, risk-based, and predictive maintenance, depending on the planning and scheduling models used.  

To estimate the expected maintenance costs, information about failure rates and costs is required for corrective maintenance, while for predetermined preventive maintenance, information about expected lifetime and costs of maintenance actions is needed. For preventive condition-based maintenance, information on component deterioration and the costs of obtaining information are necessary. 

Combining preventive and predictive maintenance 

Combining preventive and predictive maintenance can be a powerful approach to optimizing maintenance activities as such maximizing equipment reliability and minimizing downtime as well as maintenance costs. However, switching between preventive and predictive maintenance can be challenging, and some of the key challenges include:

1. Data availability and quality: Predictive maintenance relies heavily on data collected from sensors and other monitoring systems to detect potential failures. However, if this data is not available or is of poor quality, it can be difficult to make accurate predictions about when maintenance is required.

2. Maintenance planning: Switching between preventive and predictive maintenance can require significant changes to maintenance planning processes. Predictive maintenance requires a more flexible approach to scheduling maintenance tasks, as maintenance is only performed when there is evidence of an impending failure. This can make it difficult to plan maintenance activities and coordinate resources effectively.

3. Staff training: Shifting from preventive to predictive maintenance may require staff to learn new skills and work with new technologies, such as predictive analytics and machine learning. Ensuring that staff have the necessary training and support can be a challenge.

4. Cost: Implementing a predictive maintenance program can require significant investment in new technologies and equipment, such as sensors and data analysis software. This investment can be a barrier for some organizations, particularly smaller ones with limited resources.

5. Culture shift: Moving from a preventive maintenance mindset to a predictive one can be challenging for some organizations, particularly those with a long-standing culture of performing maintenance tasks on a fixed schedule. Encouraging a more data-driven approach to maintenance may require significant cultural change.

In summary, while there are significant benefits to be gained from switching from preventive to predictive maintenance, it is important to be aware of the challenges involved in making this transition. Overcoming these challenges requires careful planning, investment, and a willingness to embrace new technologies and approaches to maintenance. And we are here to support you throughout the whole transition journey with the help of our state-of the art AIH software.

How we can support you optimize your maintenance 

With the help of our Asset Integrity Hub (AIH) solution you will not only have comprehensive information on what maintenance work your asset needs but also have capability to control the time aspect of your maintenance so that all the potential failures and faults are addressed proactively before they occur. 

AIH encompasses variety of maintenance strategies including but not limited to the below mentioned ones and can combine them to address your specific needs:  

• Preventive and predictive maintenance  
• Corrective maintenance 
• Risk-based maintenance 
• Reliability centered maintenance 
• Etc. 

Request a demo now to see in person how we can help you optimize your maintenance.