Maintenance can often be one of the trickiest aspects of owning and managing a business. Is it best to approach maintenance the most traditional way, through a preventive maintenance strategy? Or is it worth investing the capital necessary to bring in the infrastructure required for a predictive maintenance strategy? To answer these questions, it’s important to understand the differences between the two methods.
Beginning with the former, preventive maintenance has made a lasting impact on maintenance strategies. Through these strategies, all pieces of equipment receive maintenance at scheduled intervals throughout the year. These intervals will vary based on some key characteristics of each piece of equipment. At the most basic level, this maintenance strategy is primarily calendar-based. The latter, predictive maintenance, is much more dynamic in nature. Predictive maintenance utilizes data from unique systems that are connected to each piece of an organization’s equipment to determine the most optimal maintenance schedule. Rather than performing maintenance when it isn’t needed, these systems save organizations a great deal of maintenance resources.
Determining which of these two maintenance approaches is right for your business can be quite challenging, but it doesn’t have to be. With the accompanying resource as a guide, the decision should become increasingly clear. The resource will detail industries or business sectors that can benefit from each of these strategies, in addition to ways in which blending them can be possible. No matter where your organization lands on the spectrum, the resource can serve as a great tool for distinguishing between these two strategies.
For any organization on the fence about the complexity of predictive maintenance, it’s worth noting that the implementation of these predictive maintenance systems have only gotten easier over the years. Namely because the more technologies that become connected with the Internet of Things, the more precise their capturing and measuring can truly be. As more and more equipment is connected to the IoT network, these systems will begin reporting the most accurate data they can. Data that can indicate when a piece of equipment can fail, what maintenance can delay this failure and much more. For the sake of uptime, predictive maintenance is unmatched.
It’s worth noting, however, that predictive maintenance does have its own flaws. Namely its barriers to entry. The most impactful is the cost associated with the systems, but much more is required out of organizations willing to integrate them into their operations. For example, all existing employees would require adequate retraining for these new systems and mastering them would take quite some time as well. A business willing to utilize these systems will require the capital necessary to invest in them, managers capable of adjusting the change and enabling their employees, as well as the technological prowess to get the most out of these systems.
For more information regarding maintenance philosophy, be sure to review the infographic accompanying this post. Courtesy of Industrial Service Solutions.
