Businesses across the span of all major industries are challenged with the task of determining the best maintenance strategy right for them. Many will opt to sticking with the most traditional maintenance approach in preventive maintenance for all of their equipment. Other organizations may be willing to invest into newer predictive maintenance systems for the sake of more fine-tuned maintenance scheduling. Finding the right balance is a difficult ask for many business, but this post should serve as a means to understanding the two different methods.
It’s likely best to begin with the former, preventive maintenance. This maintenance strategy includes operating on equipment at scheduled intervals throughout the year. Businesses will determine these variables based on characteristics of each piece of equipment, meaning some equipment will require more maintenance than others. When considering the latter, predictive maintenance, organizations are getting a much more dynamic approach. This approach utilizes data collected as a result of interconnected systems that determine the most optimal maintenance schedule based on output and external data. Rather than performing maintenance when it isn’t needed, these systems save organizations a great deal of maintenance resources.
Many organizations will fail to ever execute on their maintenance perfectly. There will always be some challenge to overcome, regardless of if you’ve been in business for 15 years or for one year. However, any organization currently struggling in determining which approach is right for them, should find some respite in the infographic paired alongside this post. Within it, the ways in which these approaches differ and the ways they can help decrease the likelihood of equipment failure for your organization are discussed in more detail.
Most organizations have their doubts surrounding the complexity of predictive maintenance. However, implementation of these systems have simplified over the years. Inherently, as an Internet of Things technology, the more equipment that’s connected to the network, the more precise their capturing and measuring can be. Any organization can benefit from data that can indicate when a piece of equipment can fail, and which specific maintenance approach can delay this failure. For the sake of uptime, predictive maintenance is unmatched.
While the benefits of a predictive maintenance system are clear, there are a number of hurdles to jump before it can solve all of your organization’s issues. The first of which is the investment capital necessary to invest in these systems. Even after mustering up the capital, short-term struggles will still exist. Managers must develop a fresh sense of mastery over these new systems, in addition to retraining their employees to make sure they can master these systems as well. Without a ‘teachable’ culture, this can be a tall order. Only after these issues, in addition to some others, are solved can the benefits be truly seen.
For any organization hoping to learn more about these two strategies, or how they can alter their maintenance resource allocation, be sure to check out the infographic paired alongside this post. Courtesy of Industrial Service Solutions.