Ensuring that any manufacturing operation continues to produce output at its maximum efficiency requires a great deal of maintenance consideration. For most organizations, their maintenance efforts are split between two different strategies: predictive and preventive maintenance. Throughout this post, both of these methods will be broken down and analyzed in detail.
Beginning with the latter, preventive maintenance is a rather customary strategy compared to predictive maintenance. This strategy is predicated on a calendar-driven system. Meaning the maintenance organizations would conduct would be based on established time intervals throughout the year. This isn’t to say each piece of equipment would require significant maintenance within these intervals, nor that all of the pieces of equipment in a fleet would be worked on at the same time. Rather this strategy is mean to establish scheduled maintenance at different parts of the year for each piece of equipment based on factors such as age and run time, amongst others.
The alternative to this strategy comes from predictive maintenance. Predictive maintenance is a much newer strategy that takes a more proactive approach than its counterpart. Rather than having a regular scheduled maintenance interval for the equipment in a manufacturing operation, predictive maintenance employs complex systems that connect to your equipment and feed you data that indicates when a given piece of equipment would require maintenance. While this approach is much more effective in terms of maintenance resources, it is also much more expensive to implement than a preventive maintenance schedule.
The downfall of this approach, though? The cost. The capital required to implement these systems is often much more than organizations care to expend for maintenance. However, many organizations around the world have broken this mold and are going the way of predictive maintenance. This change has made the implementation of these systems increasingly easier. As more and more IoT technologies begin to emerge, the more intuitive the data extracted from an organization’s fleet can be. This data would then improve the predictability of machine failure and thus the required maintenance steps to prevent said failure. For organization’s hoping to improve their efficiency and decrease their equipment’s’ downtime, this is the best bang for their buck.
However, despite these advantages, sometimes these systems are not as accessible to every manufacturing operation. The barriers to entry for these systems are often much higher than many operations can afford. They require the implementation of highly sophisticated technology platforms that must be able to fully integrate with the existing systems a manufacturing operation currently employs. This also means manufacturing managers would be tasked with retraining existing personnel on newly established maintenance policies as a result of these systems. If you believe that your operation can support the costs associated with these systems, in addition to having the trust in your employees to master these systems, predictive maintenance is likely the strategy that will provide your organization with the greatest amount of benefits.
Hoping to learn more about how either of these strategies can best fit the needs of your business? Be sure to take a moment to check out the infographic paired alongside this post for more information. Infographic courtesy of Industrial Service Solutions.