A manufacturing operations’ success is directly related to their equipment’s’ health. Poorly maintained equipment becomes improperly functioning equipment. Without equipment capable of meeting production expectations, a business will fail. Which makes the importance of a maintenance strategy that much more clear. In most instances, organizations are left to decide between two major disciplines of maintenance: preventive and predictive maintenance.

In order to understand how most organizations view maintenance, it’s important to begin with the more basic of the two approaches. Preventive maintenance is the standard approach to maintenance for countless organizations. In this strategy, every piece of equipment in an organization’s fleet receives regularly scheduled maintenance throughout the year. This maintenance is spread across a number of intervals throughout the year, largely determined by status of equipment. Meaning older pieces of equipment will likely receive more maintenance throughout the year than newer pieces of equipment. It goes without saying, then, that pieces of equipment with a higher average run time will also require more maintenance than their lesser running counterparts. While these schedules may differ, the core philosophy is the same.

The more effective strategy, however, is predictive maintenance. Everything that the preventive maintenance strategy stands for, predictive maintenance seems to disregard. While it’s true that regularly scheduled maintenance can be effective, it doesn’t diagnose or solve a problem as accurately as the systems in a predictive maintenance strategy can. Through integrated Internet of Things technologies, all of an organization’s equipment can be maintained based on equipment output and external data collected. Real time analysis allows owners and managers to develop maintenance schedules that are much more accurate than those found in preventive maintenance, making it the more effective of the two. It isn’t cheap, though.

While it’s true that the costs of these systems are much higher than most organizations can justify, their implementation continues to simplify. This is largely in part due to the number of technologies connected to the Internet of Things continuing to increase. As more and more technologies are added to this network, the more possibilities for understanding these machines become present. As of right now, these systems can provide in-depth reporting and analysis regarding performance data of connected equipment. Organizations can then more accurately predict when their equipment will experience failure and what maintenance is required to both avoid failure and prolong the health and efficiency of the machine.

Despite their advantages, as mentioned previously, cost will often keep organizations from benefiting from predictive maintenance systems. For some organizations, this inaccessibility is actually a benefit. Disregarding the cost for a moment, organizations would have to adapt in other means when utilizing a predictive maintenance system. For example, integrating these systems into existing organizational processes can be difficult. What’s even more challenging, though, is retraining employees regarding these systems. For some tenure employees, this could mean asking them to completely reconsider everything they’ve known about maintenance to the day. Certainly not an easy task for any employee. With that being said, if you believe your organization is capable of investing the capital and have enough trust in your employees to make the transition smooth, predictive maintenance is the route to take.

There’s no reason any manufacturing operation should be unsure of their maintenance options. To learn more about predictive maintenance systems, take a moment to check out the infographic coupled alongside this post. Courtesy of Industrial Service Solutions.