How Predictive Maintenance Stacks Up Against Traditional Maintenance Strategies

The IIoT is disrupting established maintenance practices with new capabilities.

For today’s industrial machine builders and automation vendors, connectivity is no longer optional. Whether you purchase a new laser cutter, robot or PLC, chances are it will have built-in sensors and connectivity for use with an industrial IoT solution.

Industrial IoT is not especially new for global corporate players, companies like Boeing or Bosch that have assets across the globe, with the budget and personnel expertise to get IoT solutions like condition monitoring, predictive maintenance and digital twin up and running. Today, thanks to the declining cost of sensors and the options available for cloud-hosted industrial IoT platforms, predictive maintenance is profitable for the little guy, too.

To find out more about how the IoT enhances Predictive maintenance, download this free research report.

Predictive vs. Other Maintenance Strategies

In a perfect world, equipment wouldn’t wear and break down. Unfortunately, maintenance is a routine part of every equipment life cycle. There are three main approaches to maintenance, involving varying levels of planning, costs, and efficiency. Below, we’ll briefly describe three other common maintenance strategies that all industrial engineers and millwrights know well.

Matt Newton, senior portfolio marketing manager, asset performance management at Industrial software provider AVEVA, described the transition from traditional maintenance strategies to predictive maintenance as part of a maturity process.

“We look at the maintenance strategy as kind of an evolutionary process. So, a customer may start off with a particular kind of asset and let it run until it breaks down. Then they go fix it when it’s broken. But as they mature in their maintenance strategy and start to adopt new types of technologies, that’s where we can start to deploy things like condition-based maintenance and predictive maintenance. Basically, it’s about helping the customer apply the right maintenance strategy to the criticality level of an asset. For example, if you have an asset that is very low cost to repair and that does not have a significant impact on business if it goes down, you may run that asset until it breaks down and then just swap it out. On the other hand, you may have an asset that’s very critical to your process and to your business, and that’s where we deploy more advanced technologies like predictive analytics,” said Newton.

Reactive Maintenance: Run-to-Fail

Under this strategy, maintenance staff prepare to fix breakdowns by keeping an inventory of common spare parts. When equipment does fail, it becomes a mad scramble to identify the problem, repair the equipment and get it back up and running. Maintenance staff must always be on-hand and ready to deal with an emergency job. Besides stopped production, equipment failure can also result in damage to other machines, tools or parts. In addition, it’s impossible for maintenance personnel to effectively manage their time.

“In all of these predictive applications, none of them are ever going to prevent a machine from breaking down,” said Robert Golightly, marketing manager, asset performance management at AspenTech. “What they are going to be able to do is to shift downtime from an unplanned mode to a planned mode. It’s been shown that emergency maintenance can be five to ten times more expensive than maintenance activities done on a planned basis.”

According to Deloitte analysis, reactive maintenance results in less than 50% OEE. For comparison, Deloitte ranks predictive maintenance at >90% OEE.

Preventive Maintenance: Scheduled Activities

Regular, scheduled shutdowns are routine in manufacturing operations. No matter which primary strategy is in use, planned maintenance will always be a part of the equation. Under this strategy, equipment is serviced at predetermined time intervals, repairing or replacing damaged equipment before it breaks down. As every maintenance specialist knows, this strategy reduces breakdowns at the cost of some redundancy. Parts replaced before failure may seem to be perfectly fine. Per the Deloitte analysis mentioned above, preventive maintenance supports 50-75% OEE.

Proactive Maintenance: Identifying Problems

While reactive maintenance is focused on identifying the cause of a breakdown of equipment, proactive maintenance is focused on identifying those causes before the breakdown occurs. For example, if a machinist reports more chatter and vibration on a certain tool, maintenance personnel can start to work on the problem before it causes a machine failure or a broken tool.

Like preventive maintenance, this strategy works best in concert with other strategies, such as planned maintenance. The disadvantage of proactive maintenance as a primary maintenance strategy is that it requires highly skilled personnel to correctly diagnose and address problems based on the warning signs. In addition, the maintenance department must be given sufficient power and agency to make the decisions required, such as shutting down a machine that appears to be running fine; ordering parts that may not be apparently needed, and other executive calls. Depending on the company culture, this may not be easy. Deloitte analysis shows this strategy delivers 75-90% OEE.

Predictive Maintenance: Anticipating Problems

Predictive maintenance analyzes asset data to predict failures weeks in advance, allowing you to make changes to production, schedules and maintenance activities in order to prevent failures that cause unplanned downtime.

Christoph Inauen is the vice president of strategy at Siemens Mindsphere. “I think what we’re seeing in the market today is that predictive maintenance for many of our customers is something of an ultimate goal. Many of those customers do not necessarily start there. Instead, they may start with something simpler, let’s say asset management or condition monitoring, and then as they get more familiar with that aspect, they add complexity and they move toward the prediction side, and then they implement something like predictive maintenance,” he explained.

To find out more about how your company can capture that ultimate goal, how much investment is required and more, download the free research report Using the IIoT to enhance Predictive Maintenance.