A manufacturing operations’ success often boils down to their maintenance strategy. With improperly functioning equipment, or equipment experiencing failure too frequently, operating a manufacturing business would be impossible. Meaning the correct maintenance strategy is imperative to an organization’s success. In most instances, organizations are left to decide between two major disciplines of maintenance: preventive and predictive maintenance.
A basic understanding of maintenance would mean you’ve likely heard of the first strategy. This strategy has been a staple in the manufacturing industry for some time. Preventive maintenance is a calendar-oriented maintenance strategy that sets up specific time intervals throughout the year for planned check-ups on each piece of equipment in an organization’s fleet. While this may seem counterintuitive as maintenance would be conducted much more often year-round, it has been known to be effective for many organizations. Determining the frequency in these maintenance intervals is what’s most important. An organization’s older machines may require a handful of checkups per year compared to an organization’s newest machine receiving a single check up on the year for example. Incorrect maintenance intervals can be detrimental to the health of any piece of equipment.
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 technology integrated into equipment 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.
Luckily for the organizations unable to afford these systems, they continue to improve as a result of organizations that can afford them. As implementation has simplified, more organizations have become willing to invest in these systems. As more and more pieces of manufacturing equipment become connected to the Internet of Things, the more potent these systems can become. Their capabilities in understanding the equipment and their failure signs expand as more organizations utilize this maintenance approach. Understanding where a piece of equipment is failing can lead to a much quicker reactionary maintenance schedule and can reduce downtime and thus improve efficiency.
Most organizations would love to jump at the benefits that these predictive maintenance systems can bring to their organization. Unfortunately, most organizations often disregard some of the additional challenges that these systems bring. Of course the cost is what stops most organizations, but those that can afford these systems will also have to mitigate some additional issues. For example, in order to get the most out of these systems, employees will need a rigorous understanding of how the platforms associated with these systems operate. In some cases, this can mean tenured employees being required to disregard everything they’ve known about maintenance in their time with an organization. Training will also be required for these systems in order to properly work alongside them. Ultimately, organizations have to consider if their capital investment will be worth it if their employees are unable to overcome the challenges associated with these systems.
For more information regarding the major differences between these two maintenance approaches and how they can benefit your organization, take some time to check out the infographic coupled alongside this post. Courtesy of Industrial Service Solutions.
