Any and every manufacturing operation around the world, while operating by different standards, would be nothing without a sound maintenance strategy. While it’s true that every operation is different, this would also mean that every operation will have some unique maintenance needs that must be met. Two of the most successful strategies that have been known to meet the maintenance needs of nearly every business are known as preventive and predictive maintenance. While they both provide quality care to equipment, they are fundamentally different in nature and this post will breakdown these differences in detail.
Let’s start with the strategy that has been the most common for businesses for some time, preventive maintenance. This strategy has been the standard for a number of businesses throughout the manufacturing industry. The way in which is this strategy works is simple: create a maintenance schedule for each piece of equipment in an organization’s fleet. These schedules are often calendar based, meaning there are set intervals for each piece of equipment in regards to maintenance. In more special instances, organizations may need to prioritize more regular maintenance for specific pieces of equipment in their fleet. For example, older pieces of equipment that still have consistent uptime may require more regular maintenance throughout the year than a new machine running half the time.
The premier alternative to this strategy is predictive maintenance. The major difference between these two strategies is the fact that predictive maintenance determines the optimal maintenance intervals based on real time data collected by the machine. So, rather than maintenance being performed on a set schedule, maintenance can be done on equipment as its needed. Which sounds fantastic, except for the fact that the systems required to accomplish this are expensive and technologically sophisticated.
Of course it goes without saying that the costs to implement these predictive systems are high, the actual implementation has never been easier. As more and more pieces of equipment find their way into the Internet of Things, the easier it becomes to more accurately track all pieces of equipment connected. The information that is able to be collected in real time as a result of these systems are what make it easier to predict the optimal maintenance period for a certain piece of equipment. For example, the performance data, surrounding temperature, or any other indicator of a machine may give managers a better idea of when this piece of equipment will require maintenance. This, in turn, leads to an increase in efficiency and less down time for organizations most important pieces of equipment.
While it may seem that predictive maintenance is the most obvious choice between the two, this isn’t always the case. Predictive maintenance systems are excellent for ensuring equipment health, but they’re not the answer to solve any bit of unexpected downtime. With such high barriers to entry, the investment into these systems is much more risky than just opting into a preventive maintenance strategy. Not only does predictive maintenance require a large amount of investable capital, they also require highly integrated technological platforms that. This means that existing and new employees alike would have to be retained with these new systems in mind. If your business has the working capital and resources necessary to make this strategy work, then it is likely the best choice.
Maintenance is often one of the toughest challenges for businesses to figure out when on their journey to long term success. If you were hoping to limit the challenges that your business will face in regards to maintenance, be sure to check out the resource paired alongside this post for more information. Resource courtesy of Industrial Service Solutions.