The success of any manufacturing operation rides on the health of their machinery. Without properly running machinery, nothing can be accomplished. For this very reason, organizations must develop a maintenance strategy to tend to their equipment accordingly. With different equipment to tend do, maintenance schedules and strategies will differ by organization. Most often, however, two separate maintenance approaches are called upon: preventive and predictive maintenance.
As the former implies, preventive maintenance, is a strategy that organizations look to in hopes of preventing unexpected downtime through regular maintenance intervals for all pieces of equipment. With these intervals scattered throughout the year, they’re often determined based on a number of key characteristics of each piece of equipment. Age and run being the two most important aspects. Meaning the oldest equipment and the equipment with the highest run time will require more maintenance throughout the year than those newer machines with far less run time.
Delving into the latter, predictive maintenance provides a more forward-thinking approach to maintenance. This strategy relies on integrated technology that is capable of reading and decoding any piece of equipment’s output data. In coordination with external data that can be impacting efficiency, businesses are capable of real-time analysis providing a look into when certain machines may require maintenance. While this strategy is clearly the more efficient of the two, it is also substantially more expensive.
The technologies in these systems are much more costly than following the traditional preventive maintenance approach. This cost is indicative of the value of these systems though, with more and more capabilities sprouting up as time progresses. These capabilities are directly related to the number of Internet of Things technologies in this space. With more technologies entering the manufacturing industry, the easier it becomes to capture, report and analyze the output data of each machine. In turn, organizations are able to more accurately predict when a piece of their equipment will fail and what maintenance is necessary to avoid that failure.
While predictive maintenance specializes in reducing equipment failure and downtime, it may not be the solution to your organization’s issues. With the costs of these systems often being too high for organizations, many will fail to ever be able to afford them. Those that are able to must face the challenge of integrating these systems into their operations. This is no easy task; in fact it will require a rigid training of existing employees. Despite all of these challenges, the innovation of these systems can all but ensure an increase in efficiency.
Navigating the manufacturing industry is tough enough as it is. If you’re hoping to reduce the struggles of your organization’s maintenance strategies, be sure to consult the infographic featured alongside this post for more helpful information. Courtesy of Industrial Service Solutions.