Top tips is a weekly column where we highlight what’s trending in the tech world today and list out ways to explore these trends. This week we’re looking at five steps to follow when devising an effective predictive maintenance strategy for your organization.
Have you ever wondered what it would feel like to be able to look into the future? Well, thanks to predictive maintenance, you can do just that!
Marketing fluff aside, if you’re closely following the latest tech news, you’ll notice the topic of predictive maintenance has come up a few times. And while this concept doesn’t have the inherent mass appeal as something like AI or the latest tech fad, it’s quietly building itself a reputation as a reliable method to minimize downtime.
Predictive maintenance, or PdM, is the use of data analytics and other predictive models to determine when a failure may occur in an organization’s asset infrastructure. This enables an organization to schedule and perform maintenance tasks in advance to ensure improved efficiency and greatly reduced downtime.
The whole point of PdM is to enable organizations to utilize their infrastructure to the fullest possible extent and schedule maintenance tasks before there is a failure. PdM has established itself as one of the best ways to reduce downtime, and while its benefits are best suited to manufacturing, their scope is a lot more vast. Here are the steps you should follow when implementing a PdM strategy in your organization.
1. Analyze your infrastructure to identify critical assets and failure areas
The data used to power a PdM model includes both present and historical data. Present data includes information relating to the normal, day-to-day functioning of the asset and can paint an accurate picture of its current performance in existing usage scenarios or conditions.
Historical data, on the other hand, can provide you with valuable insights into how the product performed under various conditions in the past and can also shed some light on previous maintenance tasks performed, like why and how they were performed.
By combining both forms of data, you can perform an in-depth analysis of your entire infrastructure to determine those critical areas that require the most focus—those devices that are at the center your whole infrastructure and can act as a single point of failure. Plus, when you’re planning on implementing a PdM strategy for the first time, it’s a good idea to focus on one or just a few assets as there is often a lot of testing involved.
2. Set up a monitoring mechanism to collect a constant stream of data
PdM is a data-driven maintenance strategy. It needs a steady stream of relevant data to work as intended, and an effective monitoring system can form a solid base for the PdM strategy. Depending on the nature of the asset being monitored, the organization should use different monitoring methods. As a fairly straightforward example, if the asset is prone to overheating, the organization could place temperature sensors or thermal cameras to ensure its temperature is in the correct operating window and sound an alarm when it comes close to exceeding this window.
Lately, IoT sensors and digital twins have emerged as some of the best means to monitor asset integrity. IoT sensors enable you to constantly keep an eye on the operating conditions of your infrastructure. As for digital twins, they allow you to create a digital replica of your asset infrastructure to monitor and run tests without having to halt operations or physically interact with the asset.
3. Devise a response procedure
Now that you’ve identified the critical assets and devised an effective monitoring mechanism, it’s time to move to the next step. When the monitoring system eventually detects a potential fault, how are you going to respond? This procedure involves clearly defining user roles, responsibilities, and the steps that should be taken in the event of a fault.
Using the data gathered and depending on the nature of the fault, the organization can devise an appropriate response procedure. If the fault is minor, you could set up automated maintenance tasks to rectify it quickly. But sometimes, certain faults may be a bit more complex and require human intervention, which could lead to downtime, albeit planned. But worry not—this is where redundant systems can come into play.
4. Implement and monitor the strategy
Think of the time immediately following implementation as an extended testing period. This is going to be your first time seeing how your strategy actually performs in real-world conditions. This stage is crucial as the real-world insights you gain can help you decide if the strategy is worth further investment and also allow you to fine-tune it to make it as foolproof as possible. What’s more, PdM is a continuous process and changes may have to be made throughout the life cycle of the asset.
5. Scale up the strategy to include more assets
Once the PdM strategy has been successfully implemented on a device, the organization should consider adding more devices to the strategy to improve the robustness and reliability of the infrastructure. And then, it’s back to square one. Rinse-repeat.
Conclusion
Of course, PdM isn’t 100% foolproof. Some cracks are bound to appear. But thanks to this technology, organizations can ensure that they’re minimizing unplanned downtime and that most of the downtime they do end up facing is of a planned nature.
And while the initial cost of identifying key assets and constantly monitoring your infrastructure can be substantial, the benefits provided by the increased operating efficiency and reduced downtime can far exceed the cost. So if you’re an organization that owns and operates any kind of critical asset, a PdM strategy could be just what you need.
