Clearly there is no one size fits all when it comes to maintenance. The optimum way forward is for companies to evaluate where they are in the Asset Performance Management journey and then choose the right types of strategies for each asset or equipment type, based on the operating scenario of each plant, the role of each piece of equipment, how it might fail and how critical it is to the overall process performance or plant availability
Armed with that information along with the cost of repair and failure, it becomes possible to put the appropriate systems in place. By looking at the strategy from a system perspective, in terms of software and technology, people and process, the most appropriate regime for managing the assets in the most cost-effective and efficient way will come to life. The key is to deploy predictive maintenance on assets where it makes sense.
So, once you have completed the "reliability basics", the foundation steps of understanding criticality, failure mechanisms, availability and cost implications, where do you go from here to deploy a predictive maintenance strategy?
Gain visibility of your data
The first step on the journey is to understand where you are at with your processes and equipment. The old maxim that ‘you cannot measure what you do not know’ has never been more apt. In a typical scenario, a company needs to understand what is the current performance of their assets. This may involve taking data that already exists at the plant level and visualizing that information to support useful decision making.
A company could marry this data with IT and maintenance management system level data to have a better view of maintenance histories paired with plant performance. In this situation, the key is often capturing data that has been previously lost and integrating it into the IT domain safely and securely where it can be manipulated, analyzed, and decisions can be made on that data.