How Responsible Maintenance Practices Impact Equipment
While each and every manufacturing operation around the world is driven by success, achieving this success is impossible without keeping their equipment in top shape. Organizations without a proper maintenance strategy, for example, would then go on to fail no matter their current status in the market. In order to keep the integrity of their equipment in top shape, businesses are left to decide between two of the major strategies for maintaining equipment: preventive and predictive maintenance. Both of which provide quality care to equipment but are fundamentally different. This post will go over these differences in detail, in addition to providing some context for which might be right for your business.
Beginning with the strategy that has long reigned over the manufacturing industry, preventive maintenance. When organizations operate under this strategy, they’re focusing primarily on scheduling maintenance based on a calendar driven approach. This means they limit maintenance for equipment throughout the year depending on the characteristics of that equipment. For example, age and overall run time are two of the most important characteristics of determining maintenance intervals the older and more time spent running, the more frequent a machine may require maintenance. The opposite could be said of a younger, less ran machine.
A newer age approach to maintenance comes in the form of predictive maintenance. This is a much more dynamic approach that uses real time data collected from a fleet’s equipment to determine the most optimal maintenance schedule. This is much more effective in regards to maintenance resources compared to preventive maintenance, as certain pieces of equipment wouldn’t require the regular maintenance that its scheduled within the preventive approach. Maintaining equipment as needed is much more effective, but the downside of these systems are the exuberant costs associated with their implementation.
How do these systems function, though? Well, through connection to the Internet of Things, these systems are capable of accurately tracking the performance and output data of all pieces of equipment connected. With this information, organizations are capable of predicting unexpected failure and can more accurately plan when equipment will require necessary maintenance. Some of the data collected by these systems is performance data, surrounding temperature data and output data. With these bits of data, in connection with many others, managers are capable of decreasing unexpected down time for organizations’ most important pieces of equipment.
Many organizations will make the mistake of considering predictive maintenance is a foolproof system. Unfortunately, there are draw backs to anything, including these predictive maintenance systems. Organizations will be tasked with a difficult retraining of current employees regarding the new systems that will have to be implemented. In addition to this, these systems are incapable of eliminating 100% of downtime on any piece of equipment. That is inescapable for any organization. It’s best to consider how capable you believe your organization truly is before ever venturing into investment into these predictive maintenance systems seeing as their barriers to entry are so high.
Before investing the large sums of capital necessary to integrate these systems into your organization’s maintenance approach, take a minute to check out the infographic accompanying this post for more valuable information. Infographic courtesy of Industrial Service Solutions.