Without a proper maintenance schedule, many manufacturing operations around the world would cease to exist. For most companies, the two most common maintenance strategies for manufacturing equipment are preventive and predictive maintenance. Despite their differences, both of these strategies possess the same goal: maintaining the health and integrity of any and all equipment.
In order to select the right strategy for your business, it’s important to understand how these two strategies differ and what benefits each provides. Preventive maintenance is certainly the more common of the two strategies. This strategy often employs a blanket maintenance schedule, meaning each piece of equipment utilized in a manufacturing operation will have calendar-driven maintenance intervals based on the characteristics of each piece of equipment. For example, a newer, less frequently used machine may only require one scheduled maintenance throughout the year. Whereas an older, little to no down-time machine, may require a handful of scheduled maintenance sessions throughout the year.
Alternatively, for companies hoping to more efficiently schedule maintenance, predictive maintenance has become a much more popular approach to ensuring the status and integrity of any piece of equipment. Predictive maintenance requires a highly integrated set of systems that connect to an organization’s machines. These systems then collect and analyze the output data of these machines to indicate when each machine would require maintenance. Much more efficient, for the companies that can afford to implement these systems. Unfortunately, the barriers of entry for these systems can be too high for a great deal of organizations.
However, despite the costs associated with these systems, the implementation has continued to become easier. As more and more machines are becoming compatible with the Internet of Things, the more common these systems have become in manufacturing operations around the world. The information from these systems that get fed to managers allow a much clearer insight than preventive maintenance would ever provide. As such, the ‘predictions’ for when machines require maintenance is much more accurately measured. This data also allows managers to better predict when their equipment is at risk for failure and what must change to avoid any amount of down-time as a result of failure.
Regardless of these advantages, more often than not these systems will remain out of reach for a majority of organizations. Their inaccessibility might not be too much of an issue, though. These systems bear a very high cost to begin, but they also require near seamless integration in order to get the most out of them. Another downside is the required retraining of existing employees to work alongside these new systems and new platforms that may be required as a result of these systems. However, if your business has enough capital to support the transition, the benefits will likely outweigh the cost. It may just take a slight adjustment period.
For additional information on the advantages and disadvantages of these two strategies, in addition to how to properly differentiate between the two, be sure to check out the featured resource of this post. Courtesy of Industrial Service Solutions.