A Guide To Directing Maintenance Resources Effectively For Your Business

Allocating maintenance resources throughout the year is often a tremendous challenge for many businesses operating within the manufacturing industry. This is largely in part due to the fact that there is no blanket solution for every manufacturing operation, each of their needs are bound to be different. Despite unique needs, most businesses default to using one of two industry accepted maintenance strategies. Those two are preventive or predictive maintenance.

Of the two, preventive maintenance is certainly the most traditional. This strategy relies on calendar-driven maintenance intervals for each piece of equipment in an organization’s fleet. The way these intervals are determined vary from business to business, but ultimately come down to two different elements of a particular piece of equipment. The age and average run-time of a machine typically dictate how often it will receive maintenance in this strategy. While this isn’t the most effective in regards to maintenance resources, it will ensure that all pieces of equipment are well maintained throughout the year.

For organizations looking to utilize a more diagnostic maintenance strategy, they often look to predictive maintenance. Despite being a much newer strategy, its efficiency cannot be denied. Instead of having scheduled maintenance intervals for each piece of equipment, organizations can instead invest in predictive maintenance systems that will be integrated into their machinery and equipment. These systems would then collect output data of an organization’s fleet and analyze it in order to determine the most ideal maintenance period. In addition to being a great precursor for maintenance, these systems also reduce machine failure through the same manner. The major con of these systems, though? Their price.

While the costs to implement these 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.

Important to note, however, is that this change will not always bring about inherent success to your organization. In fact, this change can also provide your employees with a unique set of challenges. The existing protocols for your employees would likely all be thrown out the window as new platforms would be required to be learned in order to get the most out of these predictive maintenance systems. Retraining existing employees in addition to having to train new employees with little to no knowledge regarding these systems will require a great deal of time. If your company has the capital available, coupled with the confidence to get employees up to speed, this strategy could be the right fit.

Still unsure as to where your business would likely fall between these two major maintenance strategies? More information on how both of these strategies differ and the types of businesses they’ve been known to improve can be found within the infographic featured alongside this post. Take a moment to view it. Infographic courtesy of Industrial Service Solutions.