Organizations around the world are often left to decide between two distinctive maintenance approaches for their manufacturing operations. While a majority of organizations have always defaulted to preventive maintenance, some organizations have transitioned into a more custom-made approach in predictive maintenance.

It’s important to understand the former before the latter. Preventive maintenance is predicated on maintenance philosophy that has been around for ages. The concept is rather simplistic: in order to ensure the health of any equipment, perform routine maintenance on all equipment owned an organization at regularly scheduled intervals throughout the year. Organizations determine the most optimal time interval per machine based on characteristics like age, run time and how much downtime a machine is allotted for any given year. Seems simple but is ultimately ineffective in regards to maintenance resources.

Alternatively, organizations can prioritize a predictive maintenance approach for a more effective use of their maintenance resources. Operating almost opposite to that of preventive maintenance, this approach uses sophisticated systems that are integrated into equipment to collect data that can indicate when a piece of equipment requires maintenance. Certainly much more effective, but there are some downsides. Namely the costs associated with implementing these systems.

While it’s true that the costs of these systems are much higher than most organizations can justify, their implementation continues to simplify. This is largely in part due to the number of technologies connected to the Internet of Things continuing to increase. As more and more technologies are added to this network, the more possibilities for understanding these machines become present. As of right now, these systems can provide in-depth reporting and analysis regarding performance data of connected equipment. Organizations can then more accurately predict when their equipment will experience failure and what maintenance is required to both avoid failure and prolong the health and efficiency of the machine.

A misunderstanding that many owners and managers have come to realize, however, is that predictive maintenance systems are not meant to save a struggling business. Not only are the barriers to entry higher than most organizations can handle, they also require a great deal of investment in the technology platforms that employees must use in order to utilize the systems. Following said investment, organizations have to be prepared to train their employees to master these systems which often requires them completely rethinking what they previously knew about equipment maintenance. There are bound to be significant challenges even after making the initial investment into the systems. If your organization is capable of investing the capital required and feels comfortable facing these challenges, predictive maintenance might be an excellent fit.

For more information regarding the differences between these two systems and how they can strengthen or weaken your organization, be sure to review the infographic accompanying this post. Courtesy of Industrial Service Solutions.