The cost of unplanned downtime in manufacturing adds up quickly and gets expensive fast. The detrimental result is lost production and lost revenue- two things you definitely don’t want to add to. This is especially true for unplanned downtime. On top of that, you have to take all factors into account, it affects your bottom line in many more ways than just the cost of fixing a machine or some equipment.
You lose money on inefficient time spent when equipment is down, longer project lead times impacting on-time delivery, and of course the time and money it takes to get your equipment back up and running.
The Real Cost of Downtime, is Probably more than You Think
To get to the true cost of manufacturing downtime, you have to add up all of these factors, including intangible costs which are often overlooked. Company morale and responsiveness are a couple of examples that could fall into the intangible costs category.
So, the question is: do you know how much money downtime is costing you in your factory? Some consultants believe that 80% of industrial facilities are unable to accurately estimate their downtime. It’s commonly estimated that factories typically lose 5-20% of their productivity due to downtime (source). Keep in mind these are just estimates, actual numbers for different sub-industries and businesses will vary.
How Can I cut out Future Downtime?
It’s not realistic to expect to completely cut out downtime altogether. Nonetheless, there absolutely are tools, strategies, and procedures that you can start to take advantage of to reduce downtime now and in the future.
In the remaining parts of this article, I’ll share some more downtime statistics that you might find alarming, and get into the differences between types of frequent downtime events. But don’t worry, I will also share some viable solutions that can help you to avoid downtime in manufacturing and build the most efficient environment possible.
Planned vs Unplanned downtime in manufacturing
First off, all manufacturing downtime needs to be addressed, every inefficiency has room for improvement. Whether it’s planned downtime, unplanned downtime, an expensive and frequent downtime occurrence, or a small and rare occurrence. It’s important to always drive continuous improvements and keep a proactive mindset. Fix problems before they happen.
Manufacturing downtime can be broken down into two main groups: planned and unplanned downtimes. Not all downtime is unplanned downtime.
Planned downtime is any downtime that is scheduled. This can entail changing fluids, or maybe making an upgrade to the current equipment. It could also simply be an inspection or any regular upkeep of the machine, system, or equipment.
In some cases, planned downtime is a larger issue than unplanned downtime. Inefficient processes and changeovers can result in massive amounts of lost production time.
When someone mentions manufacturing downtime, it’s common to instantly picture a machine going down, or one that’s been out or order for some time because of equipment failures. However, as I mentioned earlier- it’s important to keep all factors in mind. These planned downtime occurrences could be quietly gashing your bottom line.
More Examples of Planned Downtime
Excessive Job Changeover
Are you planning too much downtime between job changeovers? It might be tough to know if you aren’t tracking the process, and are used to the same process that has never been adjusted. This is another reason why a continuous improvement mindset is important. Get away from that “if it ain’t broke don’t fix it.” mentality, and start being proactive, be on the lookout for ways to get better.
Even multi-billion dollar corporations such as Amazon and Apple have room for improvement, and they definitely aren’t sitting around, content with their current processes. They are constantly innovating and actively looking for ways to get even better. If these companies see room for improvement, there is no reason why any manufacturer of any size should be content with their current manufacturing processes.
Excessive job changeovers can result in significant downtime. Even only a few minutes or a few extra seconds between jobs can add up quickly, especially for discrete manufacturers with higher numbers of daily changeovers.
Excessive Tool Changeover
We too often see companies stick to their old processes that were established 30 years ago and they hurt themselves by planning too much downtime, it sounds crazy when you say it out loud, but it’s a real issue in the manufacturing industry.
Excessive tool changeover times can make an impact similar to that of excessive job changeover times. However, there is an added element to tool changeovers. Over-optimizing. Could you be performing excessive maintenance? Changing out tools before they need to be? If not, how do you know?
A gut feeling? Or maybe you’re following the instructions to change out a tool every x amount of days or after x amount of use. While we commend you for staying on top of your maintenance, the odds are, this process isn’t optimal.
Predictive maintenance can be a huge help in this area. Use the data you produce every day to accurately predict when changeovers should happen, if you are being too excessive, and if you’re not performing enough maintenance, shortening the life of your machine.
Unplanned downtime occurs whenever there is an unexpected machine failure or stoppage during any stage of the manufacturing process. Unplanned downtime can happen at any moment and often occurs during changeovers.
Common types of unplanned downtime occurrences include machine or equipment failures, human operator error, unplanned machine maintenance, and changeover times.
I did just list tool and job changeovers as planned downtime occurrences. There, I was talking about planned processes that are inefficient from the get-go. Here, I’m talking about when these changeovers take even longer than the already inefficient planned process.
Machine Downtime and Equipment Failure
Machine downtime and machine failure are extremely common and frequent downtime events. The Factory floor is full of numerous machines with many moving parts. With this being the case, I don’t think anyone is surprised that machine downtime is a leading revenue killer.
On top of that, it’s not the easiest thing in the world to gain a deep understanding of how these machines work, and how to diagnose a damaged machine for root cause and issue.
What manufacturers need to do here, is find a way to gain real-time machine visibility. Start tracking certain metrics and processes and make data-driven decisions for incremental improvements. I’ll get more into this later when I talk about what you can do to cut down on the cost of downtime in manufacturing. If you want to skip right to that section, click here.
Unexpected Production Backups
Rework, inefficient changeovers, and excessive scrap among other factors all play a role when you come across these unexpected backups. This causes fewer jobs to get done each day and makes it tough to have consistent on-time delivery.
Rework can especially hurt you in this area. If you already don’t have enough time to do the job once, you definitely don’t have enough time to do it twice.
Late delivery and prolonged jobs hurt customer relationships. An unsatisfied customer isn’t going to come back, and they aren’t going to recommend you to others either. Unfortunately, in this competitive landscape, all it takes is one less than perfect experience for a customer to move on and look for better options. Reducing unexpected production backups as much as possible will help put you in a good position for returned business with satisfied customers.
How much Money Manufacturing Downtime is Actually Costing You
Spoiler alert, it’s a lot.
Some of these numbers can be hard to wrap your head around. Let’s get into it and go over some actual numbers from studies that have been conducted in recent years.
Average Cost of Downtime Across All Businesses
This study took place in 2016 and comparing it to a previous study conducted in 2014, there was a 60% increase. In 2014, the average cost of downtime per hour across all businesses was $164,000. This is already a massive amount of money, then in 2016, that number jumped up to $260,000 per hour (source). I’ll leave it up to you to determine where you think that number is today in 2022.
Translating this into a Real-Life Scenario
Let’s try to translate this into a very mild real-life scenario. Say you have a plant floor full of machines, operators, and equipment running 40 hours per week. Keeping this as a fairly mild situation, we can say that just 5% of that operating time will be downtime.
According to the statistics in these studies, that would amount to just 2 hours of downtime, and $520,000. Keep in mind this is just 1 mild week and using average numbers from 2016 that are up an incredible 60% in 2 years from 2014.
Again, we do have to keep in mind that all of these numbers we’re working with are averages in a massive industry with numerous sub-industries. With that being said, we can conclude that downtime is never cheap and no matter which sub-industry you’re a part of, downtime is far too costly to be overlooked.
More Eye-Opening Downtime Statistics
The fact that most of these numbers are general, and cover the entire $7,958,200m manufacturing industry can be a good or a bad thing. The good news is that number might be high for some manufacturing sectors. The bad news is that number might be substantially low in some manufacturing sectors. The Auto industry is especially high in downtime cost. A survey revealed that just one minute of downtime in the auto industry can amount to $50,000, with an average of $22,000 (source). What is that per hour? $3 Million. This further shows the importance of really putting effort into decreasing downtime, and proactively trying to improve your process.
How Human Error Plays a Role in Unplanned Downtime
You might be surprised to hear that human error accounts for 23% of unplanned manufacturing downtime (source). The manufacturing sector is among the highest percentages compared to the average of other sectors at just 9%.
Now, this wasn’t meant to downplay the amount and cost of unplanned downtime in manufacturing coming from the machines and equipment. Faulty and improperly maintained equipment is an extremely common cause of unplanned downtime within the industry.
Most Companies Cannot Accurately Estimate when Their Equipment is Due for Maintenance
A more recent survey in 2017 revealed that 70% of companies are completely unaware of when their machines and equipment are due for an upgrade or proper maintenance (source). This is an astonishing number. Roughly 2 out of 3 manufacturers have a hard time determining the needs of the equipment on their own plant floor.
This is another indicator of how important real-time machine visibility can be. Companies significantly underestimate their downtime or are just completely unaware because they don’t take advantage of this essential data that they are creating every day. Your machines and people on the plant floor generate data all day long, use it!
What You can do to Cut down on the Cost of Downtime in Manufacturing
It’s 2022, there’s an abundance of resources and technologies that you can take advantage of to help in reducing downtime.
One thing to always keep in mind when evaluating technology options- focus on your specific business challenge first, and leverage technology to help you get there. Don’t start with a technology solution, and then ask yourself “So, how will this help us in x area?”
Predictive maintenance falls in line with proactive, data-driven maintenance strategies that gather actual data and use the data gathered to analyze the health and condition of an asset to assist in predicting when the asset should receive maintenance.
Preventative maintenance is not predictive maintenance. Preventive maintenance is consistent and routine scheduled maintenance of machines and assets in order to keep them running optimally and prevent expensive unplanned downtime and unexpected asset failure. A successful preventive maintenance strategy requires strong strategic planning before a stoppage or failure occurs.
Both are good, but Predictive maintenance with a data-driven approach is the best maintenance strategy out there that will allow you to get the absolute most out of your equipment, without shortening its life span.
Machine learning leverages real-time data and historical data from the plant floor to anticipate what will happen next. An effective machine learning model will intelligently analyze this data to provide operators with the information they need to reduce downtime, optimize maintenance with condition-based monitoring, optimize scheduling, and eliminate any production inefficiencies.
Machine learning is not only used to prevent the bad, it’s just as big of a factor in enabling the good. It provides you with the insights you need to optimize machine performance and improve all aspects of your manufacturing process with a data-driven approach.
Digital transformation brings opportunities for positive change and higher company evaluations for business leaders.
It’s a real opportunity for change. It’s helping organizations go from point A to point B, from the current state to a future state. How do you do this? By recognizing the value of data, and then actually implementing practices, strategies, and principles to get value from data.
When you start the process of changing company culture and how the company works, then you can really start to see a positive difference. A large part of digital transformation is becoming a data-driven organization with all data coming from a single version of the truth, one source.
But, don’t forget the most important part of a digital transformation- your digital strategy. It all starts at the top. Start with your business challenge first, map it out, and create a plan. Then you can leverage data and technology to help you solve that challenge.
Beginning the process of gathering data is the answer, real-time and historical data. True downtime costs are frequently attributed to not knowing what’s really happening on the plant floor and guessing on maintenance schedules and “improvements.” Become a data-driven company. Gather data, put it in the decision maker’s hands, and make the final decision based on the data. The numbers don’t lie. Every minute, every hour of manufacturing downtime can prove to be very costly. It’s important to make it a point to reduce downtime as much as you possibly can.
With IIoT/MES and industry 4.0, you can establish a strong company culture, allow employees to get smarter, and gain knowledge on the plant floor by analyzing data. At the end of the day, this leads to happier employees and customers, improved lead times, less downtime, and more company revenue. Cha-Ching!
On the Ectobox blog, we have tons of information about IIoT, Industry 4.0, digital transformation, real-life downtime case studies, and more. Subscribe to our newsletter on the right-hand side for weekly tips and tricks in the manufacturing world. Also, feel free to contact us at any time with questions, we’re happy to help and enjoy talking about all things manufacturing.