Businesses would inevitably fail without a proper maintenance schedule for all of their equipment. Determining which maintenance strategy is right for your organization can still be a challenge, though. Deciding between two premier maintenance strategies in preventive and predictive maintenance isn’t easy, but this post should make it a bit more manageable.
Let’s begin with identifying the former. Preventive maintenance is one of the most common maintenance approaches for manufacturing operations today. This strategy is predicated on performing routine maintenance on each piece of an organization’s equipment at set time intervals throughout the calendar year. This maintenance is largely dependent on the key characteristics of an organization’s equipment. Age, run-time, existing conditions that require additional maintenance, etc. are just some of these characteristics. In some instances, equipment won’t even require maintenance within the usual time interval. Which is where the latter strategy truly shines. Predictive maintenance is a much more dynamic approach to maintaining equipment. In this strategy, organizations integrate systems connected with the Internet of Things to collect and analyze data directly from the machine to determine the most optimal maintenance schedule. These systems will indicate when a piece of equipment requires maintenance or when said equipment is close to critical failure.
While these predictive maintenance systems are much more expensive than traditional preventive maintenance approaches, it is still worth considering how each of these strategies can benefit (or harm) your business. The resource accompanying this post is an excellent tool for making that distinction. In it, you’ll find additional information regarding the differences between these two strategies, in addition to ways in which each of these systems can benefit your organization. What’s most important to remember is not having an established maintenance strategy can lead to more unplanned equipment failure.
There seems to be a common misconception that predictive maintenance systems are difficult to fully integrate into an organization’s operations. However, as previously mentioned, this couldn’t be any less true. As these systems connect to the Internet of Things, the more and more machines that join the network, the more accurate these systems’ reporting can truly be. As these systems collect more and more relevant data related to machine failure and machine maintenance, their ability to predict unexpected failure and suggest the most optimal maintenance strategies increases. These systems, in the long-term, will ensure the best efficiency and uptime for these organizations.
However, with that being said, there are a number of things stopping organizations from investing in these systems. The first being their cost barrier. These systems are not for the feint of heart, or pocket. Their cost is very high in comparison to traditional preventive maintenance strategies. Not only that, they require a great deal of sacrifice to get the most out of them. For example, managers and owners will have to retrain their employees regarding their existing maintenance knowledge to be more catered toward these new systems. Not only that, organizations will have to have the technological know-how and infrastructure to support these systems. Ultimately, while the barriers to entry might be high, the investment in the long-term is very beneficial to organizations in a manufacturing operation.
For more information on how to prioritize the right maintenance strategy, be sure to take a minute to check out the accompanying infographic shared with this post. Courtesy of Industrial Service Solutions.