The maintenance needs of every company are very different. Which is why companies have to identify a maintenance strategy that adequately meets these unique needs. For most organizations in the manufacturing industry today, the strategies fall under two main categories. Preventive and predictive maintenance strategies are used to guarantee the longevity of an organization’s fleet of equipment and machinery. This post will include details of the major differences between these two strategies.
Preventive maintenance is certainly the most traditional of the two. It has long been accepted in the industry despite some of its inefficiencies. This strategy is founded on a calendar-oriented maintenance approach, where organizations would schedule checkups on equipment throughout separated intervals of the year. Therein lies the inefficiency, as some pieces of equipment might not require the work that they’re requesting. On the other hand, some pieces of equipment might require more frequent check-ups but are being neglected as a result of this strategy. With enough attention to detail and proper scheduled intervals, this strategy can maintain equipment effectively.
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 the integration of 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.
As with anything that has such valuable capabilities, the cost is often what keeps organizations from defaulting to predictive maintenance strategies. With preventive maintenance, they’re able to save valuable capital. The organizations that have made the switch continue to contribute to the proficiency of these systems. As more technologies are added to the Internet to Things, the more accurate the interpretation and analysis of the data can become. With more data comes improved predictability, meaning machine failure would inevitability decrease. If an organization is prioritizing efficiency and limited equipment downtime, investment into these systems can be essential.
What every organization should know before transitioning, however, is that there will be some inherent challenges. Not only for owners and managers, but also for employees. For example, existing protocols may need to be dismissed to adapt to new platforms required to operate these systems. This would require some rigorous retraining and can add to the stress levels of employees. Not only that, the information in place to train new employees would be next to nonexistent which also presents a unique challenge. Companies with available capital and the confidence in their employees are the most fit to invest into this strategy.
If your organization is looking for more information regarding how each of these strategies can increase the longevity of its equipment, be sure to take some to review the resource featured alongside this post. Courtesy of Industrial Service Solutions.
