Selecting Between Two Premier Maintenance Strategies

Every company’s maintenance needs are different. In addition to their maintenance needs, every company’s maintenance strategy is unique. Most companies’ strategies for maintenance fall under the umbrella of predictive or preventive maintenance in order to ensure their fleet of equipment and machines continues to run properly. This post will detail the differences between these two strategies.

Beginning with the latter, preventive maintenance is a rather customary strategy compared to predictive maintenance. This strategy is predicated on a calendar-driven system. Meaning the maintenance organizations would conduct would be based on established time intervals throughout the year. This isn’t to say each piece of equipment would require significant maintenance within these intervals, nor that all of the pieces of equipment in a fleet would be worked on at the same time. Rather this strategy is mean to establish scheduled maintenance at different parts of the year for each piece of equipment based on factors such as age and run time, amongst others.

The more diagnostic approach comes from predictive maintenance. This strategy disregards the regularly scheduled maintenance of its counterpart. Instead, it employs a particularly complex system of technologies attached to the IoT to collect data on each piece of equipment or machinery in an organization’s fleet. This data is then analyzed in real time to indicate when a piece of equipment would require maintenance. This, in turn, makes this the more efficient maintenance approach.

The downfall of this approach, though? The cost. The capital required to implement these systems is often much more than organizations care to expend for maintenance. However, many organizations around the world have broken this mold and are going the way of predictive maintenance. This change has made the implementation of these systems increasingly easier. As more and more IoT technologies begin to emerge, the more intuitive the data extracted from an organization’s fleet can be. This data would then improve the predictability of machine failure and thus the required maintenance steps to prevent said failure. For organizations hoping to improve their efficiency and decrease their equipment’s downtime, this is the best bang for their buck.

Important to note, however, is that this change will not always bring about inherent success to your organization. In fact, this change can also provide your employees with a unique set of challenges. The existing protocols for your employees would likely all be thrown out the window as new platforms would be required to be learned in order to get the most out of these predictive maintenance systems. Retraining existing employees in addition to having to train new employees with little to no knowledge regarding these systems will require a great deal of time. If your company has the capital available, coupled with the confidence to get employees up to speed, this strategy could be the right fit.

For more information on the differences between these two strategies, be sure to check out the featured resource below. Courtesy of Industrial Service Solutions.