Data Analytics for Utilities
Downtime, whether planned or unplanned, costs the manufacturing industry hundreds of hours and millions of dollars annually. Even with downtime reduction strategies like preventive maintenance that have been used for years, the need to keep reducing downtime is growing rapidly. Now, the manufacturing industry and sectors like metals and mining are turning towards the digital landscape to optimize their downtime reduction strategies.
Downtime can result in a domino effect that costs enterprises revenue and time across multiple sections of their supply chain. According to a market research report from the ARC Advisory Group, manufacturers lose over 5 percent of their overall productivity to downtime. That translates to an average of about 800 hours – lost – each year.
And when downtime costs a facility $30K to $50K every hour, this adds up quickly. That range is the average, of course – some downtimes can cost an enterprise up to $260K an hour. A typical manufacturing enterprise may lose $10 million to $25 million a year on downtime. In total, unplanned downtime across various US process industries costs over $20 billion annually for unscheduled maintenance.
It goes beyond just a loss in revenue, too. Unplanned downtime typically leads to a supply chain disruption which can result in a failure to deliver by the affected manufacturer. Without a more rigorous downtime reduction roadmap, an enterprise risks losing customers, trust, and even relationships with other businesses.
What are the most common causes of downtime, then? And how can going digital optimize industrial downtime reduction?
Maintenance teams and production operators face common obstacles when they tackle downtime reduction. Even though there may be some downtime reduction methods already being implemented, oftentimes these categories below are overlooked. For both unplanned and planned downtime, no matter the root cause, digitalization can cut down on unplanned repairs and address the problems at their source.
Maintaining every machine in a facility can be laborious, but corrective maintenance is far more costly. Prior to industrial IoT sensors, corrective was the most available option. Trying to keep up with maintenance for every piece of equipment across a factory when each machine may vary by brand, model, year produced, type and variation is virtually impossible without the appropriate asset management software.
Wouldn’t it be useful to have all the data for when machines need to be replaced or repaired in one place? With a planned maintenance schedule, emergency repairs, overtime and other downtime costs suddenly become a thing of the past.
Beyond maintenance, equipment also needs to be upgraded, either physically or with software. Occasionally the entire machine may need to be replaced with a more modern version. Making these investments before an equipment failure occurs helps improve downtime reduction.
Along with a planned maintenance schedule, an enterprise can have a planned upgrade schedule. In order of urgency, you’ll replace or upgrade a handful of machines at a time, increasing the reliability and production speed of the entire operation. Imagine the ability to budget for smaller, less expensive upgrades in one go. With an increase in production comes a decline in the need for overtime and the ability to meet production goals with fewer employees.
Another way to reduce downtime involves keeping your employees involved. While this might be a more difficult strategy to implement, it’s certainly worthwhile. Workers can’t act as cogs in a machine, which means they can help to manually reduce downtime – or cause it.
Operators and managers can collaborate to ensure everyone is motivated and morale is high. This means setting monthly goals, keeping open and transparent communication, truly listening to staff feedback and performing consistent employee evaluations.
Think of the mentality you might have when you’re told to produce “as much as possible” for the month. Then, instead, think of how you’d feel if you were given an actual number to achieve. Picture what incentives you might want for exceeding well past that production number. It’s easy to see why setting monthly goals is much more conducive to downtime reduction.
Likewise, evaluations can give employees insight into areas where they shine, as well as areas they can improve. As long as the assessment isn’t too critical but sets a goal for them to achieve before the next one, this can motivate a worker. Worker collaboration is fundamental to an enterprise’s continued success, and it’s most effective across a connected network.
Level of Training
Finally, but also related to the employees within an enterprise, is the training level at which they can work. Employee involvement can absolutely raise those numbers, but it can only go as far as they’re trained to go. Cross-training employees on equipment they may not typically work on, and how to fix relevant equipment, are valuable steps towards downtime reduction.
Training can continue to raise morale simultaneously. Train employees on the connection between profit and downtime. Then, using their feedback, brainstorm on how downtime can be reduced. Motivation is a big productivity stimulant, and involving employees in the decision process is a terrific step to reduce downtime overall.
What is machine downtime?
Machine downtime is the time that a machine is not working, either because it has reached the end of its equipment lifecycle, it needs corrective maintenance or something else entirely. Downtime losses are the losses that occur when a company is not operating at full capacity or, in other words, when a facility experiences machine downtime. Downtime cost is the cost of lost production during this downtime.
How do you reduce downtime?
Downtime can be reduced by reducing the number of errors that occur during any phase of an equipment or product’s lifecycle. Downtime reduction can be a key focus for capital intensive industries that face significant losses due to downtime.
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