Business owners and managers alike are responsible for more than just enabling their employees to find success. In fact, they’re tasked with one of the hardest challenges of all: maintaining their equipment in such a way that it continues to be viable to use within their production processes. This is accomplished through a sound maintenance strategy, which will differ for each organization as their needs are unique. Most often, organizations are left to decide between two separate maintenance approaches, or in some cases, a combination of the two. The two maintenance strategies are known as preventive and predictive maintenance and this post will provide the most meaningful details about both, in addition to which might be best for your business.

Beginning with the most traditional of strategies, preventive maintenance has long been the standard that businesses turn to. Throughout this strategy, businesses attempt to establish calendar-driven intervals between the work that is done on each of their machines. These intervals are often determined by the characteristics of their equipment. For example, age and average run-time of a machine are often the two most important factors that allow businesses to best estimate when the machine will require maintenance. Often times this method will leave a lot to be desired, specifically in regards to maintenance resources. With that said, it can be effective in ensuring that all pieces of equipment are well maintained throughout the year.

Rather than sticking to the basics, many organizations have sought after a more effective system. One that doesn’t leave them guessing. Predictive maintenance is what they found. This maintenance strategy takes a much more data-centric approach, with its systems interconnected between the equipment in a fleet and the Internet of Things network. These systems, once connected to the equipment in a fleet, are capable of collecting performance and output data of the machine, analyzing it and providing organizations with a much clearer picture of necessary maintenance and periods of expected failure of the machine. Impressive, right? More organizations would benefit from these systems, however, the costs of them typically stray organizations away.

While there’s no real sign for the costs of these systems to decrease, what organizations can look forward to is its integrative simplicity. More and more production technologies are being added to the Internet of Things network, making it easier for these systems to more accurately predict maintenance and downtime. Just with other technologies connected to the IoT, the capabilities of these systems expand the more that are added. The analysis and reporting of these systems are unmatched in regards to predicting failure and scheduling maintenance.

Many organizations make the mistake of believing these systems will solve all of the issues they face as a result of maintenance. Unfortunately, there is no maintenance approach to eliminate all unexpected downtime. In fact, many organizations likely benefit from their lack of investment opportunity into these systems as cost is only the start of the worries. For example, every organization that does install these systems must spend the time and resources necessary to retrain their existing employees about these newly integrated systems in a timely manner. In addition to this, new employees would be unable to absorb any sort of mastery from these existing employees assuming they come on too early. All that said, if your organization is capable of expending the resources necessary to convert to this maintenance strategy, it will likely result in increased efficiency in the long term.

If your organization was interested in learning more about the two of these maintenance approaches, in addition to the ways in which they can benefit your production processes, spend some time reviewing the infographic coupled alongside this post for more valuable insight. Courtesy of Industrial Service Solutions.