If your manufacturing operations are profitable, any downtime is going to cost. But while most manufacturers understand this and seek to minimize their downtime, many are calculating their manufacturing downtime costs incorrectly, underestimating the downstream impact of idle time.
To give a sense of the scale of the problem: A comprehensive study by technology market research firm Vanson Bourne found that a majority of manufacturers—82%—had experienced at least one unplanned downtime outage in the past three years, with the average being at least two. (For most of these companies—72%—having zero unplanned downtime is a high priority moving forward into 2020.) Though estimates of the costs of this downtime vary, some experts put it at a total of $50 billion a year nationwide.
That downtime happens is not surprising by itself. What is surprising is the extent to which digital technologies are both a contributor to, and a solution for, a large number of downtime events. Getting the technology right, then, is a huge step toward getting a grip on lost revenue due to the cost of downtime in manufacturing.
What is Downtime in Manufacturing? What Manufacturers Miss
Downtime in manufacturing (or manufacturing downtime) is any period of time in which equipment, machinery, or processes cannot function, and so a portion of work cannot be done.
Some downtime is planned downtime. Some examples: A machine is taken offline every Friday for cleaning and maintenance; a server is patched and rebooted; a plant closes for regulatory inspections that were scheduled months ahead of time. These planned periods of downtime are somewhat predictable and usually worked into the cost of goods.
There is also unplanned downtime. This occurs either when there is a failure in the equipment involved, or when there is a shortage of raw materials and/or labor. In plain English: Something has gone wrong, and it has to be fixed to get the manufacturing line moving again.
What most manufacturers miss, however, are all of the ways in which downtime “ripples out” to the rest of the plant or facility. Besides the bottleneck in workflow that happens when a particular machine goes down, or an operator needs to delay work, there are a number of hidden costs that might not be obvious until they hit the quarterly financial report. Only then do we have the true cost of downtime.
The True Cost of Downtime in Manufacturing
The “True Cost of Downtime” or TDC is the total financial impact of downtime (or, sometimes, the rate of cost per hour). A TDC analysis seeks to break down this cost for a given machinery or process failure.
Besides lost production capacity, TDC should include things like:
Recovery costs. If machinery needs to be repaired, there is a cost associated. Set-up costs and cost of producing inventory to replace any damaged product also falls under this label.
Labor costs. If your operators and line workers are hourly, they are likely getting paid even when a process is halted. This is labor costs without an associated boost in productivity.
Testing and QC inspection. When a process is back up and running, you will want to do one or more test runs to ensure that everything is OK. QC inspection of product should happen, too. Both of these can take time to execute.
Excessive job changeover. Some downtime in manufacturing manifests not as a complete halt of work, but as excessive time spent in changeover and/or set-up or “make-ready.” Changeover represents time in which product is not being worked on, and so represents a kind of downtime, too. This can be a changeover in equipment, in configuration, or even of operators, if your plant runs multiple shifts. And while a few minutes of changeover here and there might not seem like a big deal, it can add up to days of downtime over the course of a year.
Downstream costs. Suppose a line is halted at the last step in making a product. Even though this is the last step from the product’s point of view, there are still many other steps to getting that product out the door and to the customer (or retailer/distributor). For example, if production is halted, you might have people idle when it comes to QC, putaway, picking, kitting, packing, and shipping.
All of these factors add up quickly, as shown in manufacturing downtime statistics. Conservative estimates put the typical cost of downtime at $10,000 an hour, but this may itself miss several of these factors. The true cost is more likely to be $250,000 an hour and up. Indeed, one 2016 survey by ITIC found that 81% of manufacturers were estimating the TDC to be around $300,000 per hour. This was a three-fold increase from an estimate of $100,000 per hour just two years earlier.
In fact, there have been several more extreme cases where extended downtime in manufacturing led to widescale layoffs, shuttering of operational plants, and asset liquidation…all just to keep cash flow going and avoid bankruptcy.
So what causes such large-scale and costly downtime events?
Don’t let downtime hurt your business this year
The 4 Primary Causes of Unplanned Downtime in Manufacturing
Obviously, technical failure, lack of raw materials, or labor issues are the three main drivers of downtime. Still, these are merely symptoms of other, more sinister problems in underlying processes. These factors tend to drive higher rates of failure in larger manufacturing organizations.
Poor maintenance and upgrade scheduling. Again, according to the Vanson Bourne report, roughly 70% of companies “lack complete awareness of when equipment assets are due for maintenance or upgrade.” Without proper maintenance and upgrades, equipment tends to fail at increasingly higher rates over time.
Safety mishaps. When employees ignore important safety protocols, or fail to use safety equipment, the results can be disastrous. A company culture that does not prioritize safety is bound to have many more of these mishaps.
Failure to track and warn. Most failures of equipment come with warning signs, but you have to know how to look for them. For example, does a particular pump or heater experience a sudden drop in pressure before it fails? Then your process should have in place something to monitor pressure in real time and alert operators when there is a sudden drop! Indeed, most pieces of equipment have such warning signs, and they should not go unheeded. Other times, you might need to find a custom solution. New advances in machine learning are making this possible in ways not possible before.
Technological complexity. As technology becomes more complex, new sources of downtime can creep into processes. For example, newer, more complex technologies can also be more difficult to operate, leading to more frequent operator error. Automation can mean that processes work away even when something has gone wrong, exacerbating and magnifying smaller problems. More distal technology, such as servers and cloud data centers, can alter or halt work, even if a given piece of machinery is fine.
Of these four, technological complexity is the one that is most routinely missed. Fortunately, it is also the one that is most easily fixed by outsourcing technological expertise.
The Growing Role Technology Plays in Manufacturing Downtime
When it comes to downtime, innovative technologies are often both the burn and the balm. The increasing complexity in technology creates more points of failure, and so more opportunities for downtime to occur. But new technologies can also be used proactively to predict, prevent, and mitigate unplanned downtime.
So how does technology contribute? Here are just a few examples:
Server downtime. Many machines are now connected to networks, and some critical operations might depend on traffic with internal servers and data centers.
Cyberattack. Connected machines can also be vulnerable to cyberattacks that can delay or suspend functioning. These should be monitored by a Security Operations Center (SOC).
Faulty patching. Many machines used in manufacturing today have operating systems and applications that automatically update themselves. While patching is a good idea when it comes to cybersecurity, a bad patch (or a poorly deployed one) can grind things to a halt.
Power “hiccup”. Power failure can affect machines, networks, and data centers. While most facilities have backup power available, it’s not uncommon for some key pieces of machinery to restart once power is lost and before backup power becomes available, causing a “hiccup” in production.
Operating error. If operators are unfamiliar with newer controls, the chances of making a costly mistake can skyrocket.
Automation error. Automated processes that are not configured correctly, or that continue to operate in the face of problems, can destroy huge amounts of product and machinery if not caught immediately.
So How Can Technology Prevent Downtime?
All that said, technological problems often lend themselves to technological solutions. Advances in cloud technology and other kinds of digital transformation are radically altering how manufacturers approach downtime and its associated costs. These include:
Advanced monitoring. IoT-enabled devices are making it easier to get real-time data from the manufacturing floor. Advanced analytics and machine learning are making it possible to predict equipment failure and process delays far in advance of them actually happening. As a quick maintenance changeover is often faster and less costly than a full equipment failure, monitoring can save millions.
Zero-disruption upgrades. Many software platforms are turning to upgrades that can be put into place seamlessly without affecting workflow, without machines or servers requiring a restart. Upgrades that absolutely require a restart give operators the option of when to install the upgrade.
Private and hybrid clouds. Hosting applications and infrastructure in the cloud helps maintain network uptime and scale resources intelligently. Patching and upgrades can happen once without deploying throughout the network in waves.
Remote support. When shifts run 24-7, the need for tech support is around-the-clock as well. Knowledgeable support staff need to be able to address operators’ concerns at any hour of the day. Fortunately, today’s communications technology makes it possible to tap into a pool of experts remotely, any time of day, from anywhere around the world.
Cloud Manufacturing (CMfg). This is an approach to manufacturing that views resources and capabilities as services that can potentially be managed, shared, and distributed across a network. It is, in essence, the culmination of all of the above, integrated in a single distributed framework. It can help reduce costs, scale production, automate production schedules, and ultimately make manufacturers leaner and more efficient.
Progress in technology is inevitable, but it is becoming increasingly clear that manufacturers cannot maintain the needed technical expertise in-house. The future of manufacturing depends, then, on manufacturers’ ability to outsource this expertise and collaborate to prevent and mitigate catastrophic unplanned downtime in the future.
For more on the benefits of the cloud for businesses, see our articles “Benefits of Cloud Servers” and “The Top 5 Benefits of Cloud Computing for Businesses.”