Prioritizing a maintenance schedule that fits the unique needs of any organization is a challenge. However, it is one that must be overcome to ensure any organization’s success. Most organizations within the manufacturing industry decide between two strategies: preventive and predictive maintenance. While they’re both very different in the way they handle maintenance, their goal is the same: keep equipment in a functional state for as long as possible.
When you think of a typical maintenance schedule, you’re thinking of preventive maintenance. This has long been the standard for maintaining any piece of equipment’s integrity in the industry. The process is simple, schedule maintenance for every piece of equipment in an organization’s fleet at regularly scheduled intervals throughout the year. Organizations determine these intervals based on their equipment’s age, run time and any other prior conditions that impact the equipment’s health.
A much newer strategy hopes to eliminate any incorrect maintenance intervals by eliminating these maintenance intervals. Predictive maintenance systems completely disregard the calendar-driven maintenance approach. Instead, this strategy utilizes integrated technology to determine the most opportunistic maintenance intervals. These systems determine the most optimal maintenance times through live collection of output and external data of the connected equipment. This provides a real-time analysis of the equipment and can help determine when failure will occur and what steps can be taken to avoid said failure. While it’s true that this strategy is much more effective in regards to maintenance resources, it comes at a very high cost.
While they may not be getting any cheaper, these systems are certainly becoming easier and easier to implement. Largely as a result of becoming so common in the industry, these systems have opened up the Internet of Things capabilities offered to the equipment commonly used by organizations. The more machines that become connected to this network, the more accurate the data that is being reported back to owners and managers become. The more accurate the data, the more likely the maintenance that is being conducted is the correct maintenance and should prolong the equipment’s life.
While it’s widely understood that the barriers to entry for a predictive maintenance strategy are high, what some organizations fail to realize is that they require a great deal of sophistication to operate as well. Meaning organizations will have to be capable of investing the capital and training their employees to master these systems in order to justify the investment. Unfortunately, for many organizations, this can be an impossible challenge. Organizations capable of investing this sort of capital would have to be confident that their employees could make a meaningful effort to adapting to these systems. While the training might not be easy, if you believe your employees can perfect their transition, a predictive maintenance system might be the right call for your organization.
Any organizations considering investing into predictive maintenance systems should be sure to check out the featured infographic featured alongside this post. More details regarding these systems and their capabilities are included. Courtesy of Industrial Service Solutions.
