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Welcome back to TST again, Troubleshooters! Thanks for spending this time with us.
Today we’re looking at strategies for lowering manufacturing maintenance costs while reducing equipment failure and operational downtime. But first, three downtime stats that might surprise you…
Did you know?
- Unplanned operational downtime costs US manufacturers $50 billion each year
- 42% of this downtime is caused by equipment failure
- The average cost of equipment downtime (across all businesses) is $260,000 per hour.
If you’re a manufacturing exec, you may already have a pretty good idea how much downtime hurts your production numbers. And you know that maintenance, in one form or another, is key to preventing and/or mitigating a lot of that lost production and expensive downtime due to equipment failure.
But, there are a lot of choices these days when it comes to the kind of maintenance approach you implement. It’s worth some thought and research, because, according to Deloitte, inadequate maintenance strategies can reduce a facility’s overall production by 5% to 20%. The flip side of that, of course, is that a good strategy can improve your production by the same 5% to 20%.
Today we’re talking about three different types of manufacturing maintenance approaches: preventive, predictive, and condition-based. The best known of these is condition-based (sometimes called reactive) maintenance, which is the repair or maintenance that take place after a breakdown has occurred, like changing a tire after it blows. Preventive and predictive maintenance are newer approaches that are often thought to be the same thing. (They’re not.)
Preventive versus predictive maintenance
Preventive and predictive maintenance are both proactive approaches to maintenance designed to keep production machinery running smoothly by catching and repairing problems before equipment failure and downtime happen.
Both preventive and predictive maintenance are considered types of scheduled maintenance, because they are planned in advance to take place at a convenient or inexpensive time, such as at the end of a production run. This is the biggest way they both differ from condition-based maintenance, which happens after an equipment failure has already disrupted production.
Preventive maintenance, like condition-based maintenance, is not a new idea. Anyone who has taken their car in for its 5,000-mile service has been using preventive maintenance. Essentially, any maintenance that is regularly scheduled, whether the machine needs it or not, is preventive. Changing your oil every 5,000 miles might be more often than your car absolutely needs to keep functioning well, but it will keep your engine from seizing and having to be replaced. In the same way, regular maintenance of manufacturing equipment will keep the line operational for a greater percentage of the time than if you wait for failures to happen and then repair them. The US Department of Energy has estimated that using preventive maintenance can save a business 12% to 18%.
Unlike preventive maintenance, predictive maintenance is not done regularly, whether needed or not. It is performed in response to an early indication of a problem. In a predictive system, data is shared by IoT-connected devices such as vibration or temperature sensors to reveal potential problems early, so that maintenance can be scheduled for the earliest convenient time, but still before the problem becomes serious. Predictive maintenance saves manufacturers money in labor and materials costs because maintenance tasks are only being performed when they are needed. McKinsey and Company estimate that predictive maintenance could reduce maintenance costs between 10% and 40%, cut a company’s downtime in half, and reduce equipment investment costs by 3% to 5%. The US Department of Energy says that predictive maintenance has the potential to save manufacturers 8% to 12% over preventive and 40% over reactive maintenance.
On the other hand, start-up costs can be prohibitively high for smaller and medium-sized businesses. There are also technological challenges such as installation of sensors, extraction of information, and preparation of maintenance models and activities.
A comprehensive maintenance strategy
What’s the best approach for your company? It’s not necessarily an either-or decision. Manufacturers should consider a comprehensive strategy that uses the aspects of all three approaches that provide the best fit with their operations.
Preventive maintenance has no large up-front costs, is easy to implement, and can ensure that many issues are discovered and fixed before they become serious. Of course, there will be a cost attached to the unnecessary maintenance. Companies need to find that sweet spot where the cost of the regular, proactive maintenance is more than offset by the financial gains of reduced downtime (and still less than the cost of implementing a predictive system). It’s noteworthy that 80% of maintenance personnel—the people in the trenches—think that preventive maintenance should be part of an overall maintenance strategy.
Predictive maintenance is the way of the future. It harnesses the awesome power of the IoT, and has the potential for greater cost savings than preventive maintenance, but there are still a few challenges and not all manufacturers can implement it yet.
For the foreseeable future anyway, condition-based maintenance is also going to be a reality. Neither preventive nor predictive maintenance are anywhere near preventing equipment failure or downtime 100% of the time, so there are still going to be breakdowns (including of the sensors themselves). When those inevitably happen, it’s still going to cost a massive amount every minute the production line is down. So, a third and critical prong of a serious maintenance strategy is to employ well-trained maintenance personnel who can diagnose and repair electrical faults quickly, safely, and efficiently. In addition to reducing downtime, skilled maintenance professionals also save manufacturers time and money by not replacing costly parts that could be repaired, and by avoiding further injuries and accidents and damage to costly equipment. That’s the final piece of the maintenance puzzle.
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