Without a proper maintenance schedule for all of their equipment, any manufacturing business is destined for failure. Unfortunately, mastering the art of maintenance is no easy task. It requires determining which maintenance strategy is right for the needs of your organization. Most often, the decision is made between two premier maintenance strategies: preventivepredictive maintenance. With the help of this post, any struggling manufacturing manager should be more comfortable deciding between the two.
It’s best to begin with what’s widely considered as the textbook definition of maintenance for any organization. Preventive maintenance being one of the most common maintenance approaches for any operation, this strategy entails performing routine maintenance on each piece of an organization’s equipment at set time intervals throughout the calendar year. Deciding these intervals is up to the ownersmanagers of the operation, but is mostly made based on characteristics like age, run-timeother existing conditions of equipment in a fleet. Where these intervals fail is where the alternative method to maintenance flourishes. Predictive maintenance being the more dynamic approach to maintaining equipment, this strategy includes integrated systems connected to the Internet of Things that collectanalyze data directly from the output of the connected machine. With this data, the most optimal maintenance schedule can be truly determined. These systems will indicate when a piece of equipment requires maintenance or when said equipment is close to critical failure.
What most organizations fail to realize is that these predictive maintenance systems are much more expensive than traditional preventive maintenance. However, the investment is met with much better results in regards to avoiding unexpected downtime. The resource featured alongside this post can help determine whether or not your organization should ever invest into these predictive maintenance systems. The information regarding the differences between these two strategies, in addition to ways in which each of these systems can benefit your organization is also included within the resource. Most importantly, businesses will want to be sure to have some sort of maintenance schedule in place to avoid unexpected downtime.
The organizations that are hesitant toward investing into these predictive maintenance systems tend to have a hard time believing they’d easily integrate into their operations. The nature of these systems should discredit this hesitation, though. Being as though they’re connected to the Internet of Things network, as more machines join the network, these systems become more capable of analyzingreporting on the equipment they’re connected to. With this data, machine failuremachine maintenance schedules are much easier to predict. These systems, in the long-term, will ensure the best efficiencyuptime for these organizations.
It isn’t just doubt stopping these organizations from investing into these predictive maintenance systems. Another factor that slows down these investments is their cost barrier. Only organizations with ample pockets will be able to afford these systems as their cost is much more expensive in comparison to traditional preventive maintenance strategies. Capital isn’t the only requirement, though. In fact, most businesses will ever fail to get the most out of these systems as their employeesmanagers will be completely unversed in the way that they operate. New training coursesmastery will have to be acquired in order to see these systems perform to their highest capability. Not only that, organizations will have to have the technological know-howinfrastructure to support these systems. Short-term, these systems can cause catastrophic failure if not prepared for accordingly.
If your organization is hoping to avoid this failure, or are considering how these systems can benefit your operations, continue reading on for more valuable information from the resource accompanying this post. Courtesy of Industrial Service Solutions.
