Machine Downtime by the Numbers: What Maintenance Teams Need to Know
We live in a world that expects and demands on-time delivery of goods and services. Amazon’s two-day shipping standard has set a tremendous bar that other retailers have to match in some way, shape or form. While expectations may not be as great for large shipments of parts, supplies, and raw materials, they have to be delivered on time to meet demand. If they aren’t there on time from your company, another business that can get it there will snap up that customer.
On the staffing side of this equation, U.S. manufacturing is experiencing a hefty challenge with finding skilled workers. If companies can’t keep workers employed and occupied, those employees have options elsewhere. These and other complicated effects happen when machines that produce, harvest, and ship goods fail on the job. After the initial impact, the effects continue to ripple out, affecting local, regional and global economies.
This scenario would ring true if a massive machine network were to break down, or something as critical as the electric grid or internet were to go down for a week, but what about seemingly simple breakdowns or glitches for smaller but still critical business operations?
The numbers might surprise you. We rounded up some comprehensive studies to put together a reality check on the effect of machine downtime, and how your maintenance or reliability team can get proactive to reduce downtime — and cost — and stay one step ahead of the competition.
Here’s what you will learn:
- Machine downtime costs examples for businesses, by the numbers
- Downtime costs broken down by industry
- How to understand the ripple effect of downtime (beyond the first wave of costs)
- How crunching the data can help
- Why data quality matters, and how the right technology can help
- Case studies of major incidents and their costs
- Why maintenance teams are in the hot seat
The Machine Downtime Story, by the Numbers
Everyone has heard the saying that numbers don’t lie. With machine downtime, it’s all about the numbers. Here are some that are very telling.
One study by ServiceMax covering business downtime found recently:
- 82% companies had problems with unplanned downtime
- Achieving zero unplanned downtime is the highest (or a very high) priority for 72% of companies
- Over half of all companies do not completely understand or are not aware of when their equipment needs
- The cost of downtime is staggeringly high for companies–$260,000 per hour across all industries.
IIoT World highlights a few reports covering the cost of downtime in manufacturing:
- Of the 82% of companies that had issues with unplanned downtime, that downtime lasted on average four hours and cost around $2 million
- Only 24% of machine operators stated that they used a predictive maintenance plan
- Unplanned downtime can cost a company up to $260,000 an hour
Some of the takeaways from these numbers include 1) that not all downtime is equal, 2) it has different effects that are not restricted solely to the companies in question, and 3) that it leads to significant issues for the company in question’s customers.
And it’s not always large, production-driving machines that cause the issues. Slow websites and computers pose a similar set of challenges, particularly for companies that do a large amount of business over the Internet. If you are one of a rising number of companies using the Internet of Things, that’s yet another new network of machines that can break down.
The Cost of Downtime: A Breakdown by Industry
When pulling together data, we found that the numbers painted a chilling image of the true cost of downtime across industries. The findings are striking, with industries losing billions of dollars annually.
According to one study from ITIC ,98% of organizations report that a single hour of downtime costs in excess of $100,000. On average, manufacturers deal with up to 800 hours of downtime annually. There are approximately 295,643 plants in the United States, which means that downtime has lasting economic impacts across the manufacturing industry
The average truck driver drives 45,000 miles per year, while 36 million trucks are registered for business purposes. For every 10,000 miles on average, a truck breaks down or requires maintenance. Each breakdown can cost up to $760 per day on average. Each year, downtime could cost the fleet industry upwards of $123 Billion!
The Different Factors Behind Machine Downtime
Some of the major factors behind machine downtime include:
- Unawareness about the company’s machines
- Lack of proactive behavior
- Unwillingness to change set patterns
Lack of awareness
The first factor behind unplanned (and planned) machine downtime is that people don’t realize that they need to maintain their equipment or how much maintenance the equipment actually needs. The study linked above found that about 70% of companies lack awareness of when their equipment needs maintenance, checks, or upgrades.
Next up is a lack of proactive behavior. Fero Labs found that manufacturing companies simply disregard 98% of the data that they have on their company as a whole. Reasons cited included a large lack of resources to study, ingrate and act on that data. This is problematic because that data offers insights into ongoing issues that are not being solved. In many cases, these problems likely loop back around and around, but are continually ignored until surprise! The machine is down.
Resistance to organizational change
Finally, in many cases, companies may not want to change. If the company wants to change, the individual plants, facilities, and in some cases, employees may resist improving or updating their maintenance practices. They may not want to integrate preventive maintenance into their existing plans. This can have an invisible yet significant contribution to machine downtime.
However, it’s worth noting that all of the above is about companies. How can concerned individuals and companies find out what the true impact of downtime is?
How to determine the long-term effects of equipment downtime
Every time a machine goes down, it can be compared to throwing a stone into a pond. The ripples or waves push out and eventually hit the shoreline. If multiple stones are thrown, the waves get bigger and bigger. In some cases, they can take a bite out the shore if they get to be large enough.
To find out what the impact of machine downtime is, you need to look at the ripples caused by the initial impact and the effects that they have through the pond. What are some of the ways to do this?
The short answer: You need to look at the data to determine what the effects are now, and what they will be in the future.
Collecting the right data
Before diving into the data, it’s important to remember that the data sets that are studied will be different depending on the situation. For example, if you are looking at the impact that machine downtime has on an individual plant, you would look at the data from that plant. Depending on the study, you would probably get very detailed data to study.
On the other hand, if you looked at all your plants to calculate the overall impact of unplanned downtime for a global company, the data set will probably be at a higher level. It may also use less data from each plant and be more concerned about the trends that every single plant exhibit.
That being said, here are some of the different data and data sets that could be collected by companies:
- How much downtime a particular piece of equipment causes over its lifecycle
- How much planned downtime machinery requires
- How often maintenance is performed, where it happens, and the results
- What the effects are on your customers when essential machines break down
- What the effects are before and after implementing a preventive maintenance plan
- And many more.
Once companies have these internal data sets, that’s when the analytical side comes into play and begins observing the different trends that the data displays.
Use a CMMS to learn the hidden costs of downtime
After the data is collected, it’s time to see what it has to show. Depending on the forms in which it was collected, it may have to be organized first. No one really wants to try to convert data from obscure measurements in their heads or to try and teach people how to read it.
This is when Computerized Maintenance Management Systems (CMMS) that use sensors that hook into your central database can save you a lot of time. They can also significantly improve overall accuracy of your data and prevent unintentional picking and choosing. Additionally, they can uncover the costs associated with each hour of downtime, giving you the insights to reveal how much exactly every hour of lost production could be costing you and your team.
There’s not much else to say about analyzing data sets. Each company does it a bit differently, depending on their systems and needs. The important takeaway is to strive for accuracy and clarity during this process.
Make financial forecasts for future instances of machine downtime
Finally, after your data sets are collected and assembled, you can make predictions about the future. The first prediction that almost every company makes when looking at their downtime data sets is that downtime costs or will cost a lot of money.
As for the impacts on the economy? They exist, but they are hard to quantify. Perhaps the best way to quantify the effects on the economy is to take the effects that various companies are experiencing and study those.
Real-World, Real-Time Examples of Machine Downtime
With the statistics and numbers in front of us, it’s clear that the impact of machine downtime is significant. But it can be hard to see the true impact and ripple effects from a list of numbers. Here are some cases recent and not so recent where machines went down–and in some cases, stayed down–long enough for these impacts to have an effect.
NotPetya: The Code that Crashed the World
In the summer of 2017, a small snippet of code brought the world’s largest shipping conglomerate to its knees. The ripples from that crash reached across the world, impacting everything from employees on-site, to computer systems throughout Ukraine and beyond into the global theater.
Semi-trucks backed up. Terminals were dead. The entire system was frozen, trapped in the clutches of a “massive, coordinated cyber invasion.” Ten frantic days after the first computer outage, the company Maersk was just beginning to put itself back together. And the full story is still unknown.
Company estimates put the total cost to Maersk at about $300 million dollars. It’s widely suspected that it cost much more than that, all told. The company Merck told its shareholders that NotPetya cost them around $870 million due to the malware. FedEx lost $400 million, as did the French construction company Saint-Gobain. The impact was staggering.
Electrical and power outages across the United States cause machine downtime
In the U.S., power outages alone are a significant source of downtime that’s due to antiquated or worn equipment. It’s been estimated by industry sources that somewhere between $50 and $100 billion would be needed to completely overhaul it. That kind of price tag really makes people think: how much do these outages actually cost?
That number is difficult to find. Estimates rely on the length of time and who’s affected. Some rough numbers include:
- Four hours without power: $10,00-$20,000
- The cost of Hurricane Harvey: $125 billion
- The annual cost of electrical and power outages for the batch manufacturing industry: $150,000 per facility
- The estimated total annual cost range for all power interruptions: $22 billion to $135 billion
- Over half of consumers said that they would pay up to 10% more not to deal with power outages.
The Costs of IT Downtime
The two examples above are not wholly reliant on machines or equipment. In both cases, there are infrastructure problems that added to the cascade of issues, challenges, and eventual downtime. What are some examples that exist specifically because machines and/or equipment went down?
Well, if Google is down for any length of time, bad things happen. In August 2013, as a result of Google going down for two to three minutes, Internet traffic dropped by 40%. Imagine if that had gone on for thirty minutes! Some things that would happen include:
- All Gmail accounts would freeze
- Google Maps would shut down, leaving drivers stranded
- Companies that depend on Google services will be left in the lurch
- People around the world would be outraged
- And many industries would experience forced downtime
How about when IT systems, in particular, shut down? On average, each minute of IT downtime costs $5,600. And that’s only the average. Because companies operate very differently, the costs fluctuate. In general, when IT machines (servers, computers, etc.) go down, the hourly range will be somewhere in the tens of thousands of dollars on the lower end.
Understand the Assumptions
To put the story of machine downtime into perspective you need to understand the assumptions we are making about downtime.
The first assumption is that machine downtime is almost always negative. While this may be the case across the board, it’s important to realize that certain industries may actually need machine downtime, in order to function at productive levels. For example, if the company only needs to use the machine once a week and this machine is a little slow; however, that time is used in other areas, as the machine is booting up. That may not be negative for that particular company.
We also assume that companies would be able to handle increased production as a result of reducing machine downtime and that their facilities could handle it. This may not always be the case.
And finally, the most important assumption is that companies should and want to improve their machine downtime. For many companies, this will be true. For other companies, however, the demand may not call for increased machine efficiency. Each company will have to evaluate what impacts machine downtime has on them and their ecosystem before making any decisions.
Machine Downtime and Progress: Maintenance In the Hot Seat
Machine downtime is the next major frontier that most companies are facing on their march towards progress. And there are a lot of large and small hurdles in the way.
One hurdle that everyone can work on is the lack of maintenance. Skipping a check that should be done, pushing technicians to hurry things along, and neglecting to maintenance equipment are all fixable problems that also significantly decrease downtime.
Another solvable issue that contributes to downtime is lack of awareness about existing equipment. While many companies consider this to be a waste of time, the effects of downtime are clearly nothing to sneeze at.
At the end of the day, two proverbs hold very true in the world of downtime. The saying “for want of a nail, a kingdom was lost” highlights the necessity of making the small changes as soon as you know that you need to. The other proverb “Rome wasn’t built in a day” counsels patience and understanding as you make the needed improvements.
Everything is a process. From the first time that a company implemented a new piece of equipment or their first machine to the last time that machine or equipment did its job, machine downtime will happen.
It’s up to each individual company to decide how they will reduce it.