Looking to Advance your EAM Maintenance Strategy? Consider These 4 Tips

If you are in charge of an industrial manufacturing business, then without a doubt you are always seeking ways to advance its efficiency alongside its productivity—and much of that relies on your maintenance strategy.

Here at DigitalThinker, we are big proponents of preventative maintenance and in this post, we are going to examine how it is key to monitor your assets in such a way where you are able to identify and correct problems prior to equipment failure—and how preparing and predicting the future has a foundation centered on your ability to harness your data collection practices today.

The Objective

Within the industrial manufacturing sector, the objective of maintenance is always focused on guaranteeing equipment reliability and uptime. It is imperative that you know how machines are working, when they are toeing the line in terms of limitations, and when new equipment must be budgeted for and purchased.

However, accurate equipment forecasting requires data capture, identification, and review within your EAM platform.  When you are able to truly understand the data that a platform like Hexagon EAM places at your fingertips, that is when you are able to realize high-quality performance.

So, how do you get to a place where you are able to predict the potential for breakdowns prior to them happening?  How do you collect and study data to attain insight that enables improved decision making?

Consider these 4 critical steps you need to take right now in the development of a proactive maintenance program.

  1. Data Capture: It’s never a bad time to start collecting data. And at this point, don’t worry about what to do with it, just start gathering it. Begin small and build upon that. For instance, begin scheduling bearing temperature or pump pressure checks. Plan these out at regular intervals and record the measurements while also sticking to the schedule. If you are able to capture real-time data via your EAM platform, then this allows an advanced approach and will improve your accuracy.
  2. Evidence Review: Once you have your data in hand, study it. Check to see if any patterns are visible that could present an issue or align with operational problems you have been experiencing.  And ultimately, the longer that you engage in data capture, the more knowledge you are going to be able to glean when you review it. You will be able to compare data you capture with historical data sets where failures have occurred.
  3. Identify Opportunities for Improvement: After you analyze your data, then you can begin to make predictions about where failure could occur and you can improve your decision making—in real-time no less—and ultimately avoid machine failure and the downtime that accompanies it. Then, you will be able to create a strategy that allows you to prioritize equipment that needs to be repaired, ensure critical operations are covered, and augment specific operating processes. Once on top of it, you will be able to better plan for downtime and there will be fewer surprises and emergencies.
  4. Evaluate: At the end of the day, your data is only as good as your process is for using it. To truly understand its power, it is necessary for you to visualize and understand it. This means being consistent in your processes, taking time to evaluate what the data is telling you, and then, create your own hypothesis on where problems could lie.   And if you have the potential to better use the platform you are collecting data on, then all the better. That is what Hexagon EAM is made for.

To learn how you can take better advantage of Hexagon EAM and its capabilities, or to simply understand how this platform could improve your business, reach out to the team at DigitalThinker today. We are passionate about helping manufacturing organizations get the most bang for their Hexagon EAM buck, and we would love to help your organization be successful.