In order to ensure any manufacturing operations’ success, businesses must be willing to invest in the most rigid maintenance systems. The right maintenance schedule is imperative to maintaining any piece of equipment’s life and longevity. For most organizations, two of the major disciplines of maintenance are preventive and predictive maintenance.
The former strategy is likely the most common of the two. It is a common staple for maintenance in many industries around the world. Preventive maintenance is a strategy that includes performing maintenance on each piece of equipment in an organization’s fleet at routine intervals throughout the year. This may seem counterintuitive at first, but the truth is for a majority of organizations it is effective. The frequency at which machines receive maintenance is largely based on age and average run-time. For example, older machines may require more maintenance throughout the year than newer machines. The same way that machines that have a longer average run-time will likely require more routine maintenance than those with a shorter average run-time.
Recent developments have brought about a newer, more forward-thinking approach to maintenance. Predictive maintenance systems employ a strategy that includes integrated technology into a businesses’ fleet of machines or equipment. This technology then reads and decodes the output data, in addition to external data that can be affecting efficiency, of an organization’s fleet for a more real-time analysis of when certain machines may require maintenance. While this strategy is clearly the more efficient of the two, it is also substantially more expensive. For most organizations, these systems can even seem unobtainable.
While the cost of these systems remains high, the implementation of these systems has never been easier. As more and more technologies find their way into the Internet of Things ecosystem, the possibilities continue to expand. The moment these predictive maintenance systems are installed, they’re able to capture and record performance and external data of an organization’s fleet. This data can then be analyzed to provide insight into when a particular machine may require maintenance in addition to revealing the problem area that requires maintenance. Which in turn leads to greater efficiency as a result of less downtime required for critical machines.
While the benefits for these predictive maintenance systems may seem staggering, it’s equally important to consider where these systems fall short. With such high barriers to entry, not many businesses can justify the cost in regards to their estimated risk. In addition to high start-up costs, these systems also require a critical understanding of new technology platforms that your employees have no knowledge of. In other words, your employees will likely face a rigid training course in order to properly work alongside these systems. This sort of challenge is not easily overcome and will likely require a great deal of time. However, if your organization has the capital and other resources available, predictive maintenance is likely the best strategy to default to.
If your organization is currently considering the switch to predictive maintenance, or you’re just looking for alternatives to your current maintenance strategy, be sure to check out the featured resource below. Courtesy of Industrial Service Solutions