How much is equipment failure costing you? For manufacturing companies, it’s literally a million-dollar question.
Unplanned downtime is extremely expensive, in terms of both direct and indirect costs. Just how costly? Here are some jaw-dropping statistics.
How much is equipment failure costing you?
- The average cost of unplanned downtime was $260,000 per hour, according to a 2016 report by the Aberdeen Group.
- Unplanned equipment downtime incidents lasted for four hours on average, resulting in a total cost of over $1 million per outage, according to a Vanson Bourne Research study.
- Most organizations surveyed by Vanson Bourne experienced at least two episodes within the past three years, costing them over $2 million.
- As a result of unplanned downtime, 37% lost production of a critical asset, and 21% lost business.
Those numbers alone should be enough to make you nervous. And they don’t even factor in the cost of lost productivity or sales. Most likely, your true downtime cost (TDC) is even higher.
What are the ripple effects of equipment downtime?
True downtime cost factors in other expenses, including lost production and the cost of parts, shipping, and labor.
Broadly, these can be classified as direct, indirect, and opportunity costs.
Direct costs include detection, containment, and recovery costs—the money spent investigating issues, making temporary fixes, and hiring service personnel to restore operations to their baseline performance.
Indirect costs include the cost of labor, overtime, and legal or regulatory fines.
Opportunity costs are often intangible, but they can have a significant impact on your bottom line. Those costs include lost time (calculated as the percentage of equipment downtime compared to total time available) and lost revenue.
Some equipment failures can also present serious safety issues, which can result in injury or even death. At the very least, they can result in fines from OSHA.
What causes equipment failure in manufacturing?
Understanding why equipment fails is crucial to reducing equipment downtime costs. While many equipment failures occur due to deterioration resulting from age or overuse, other failures are more complex.
In 1978, two American engineers at United Airlines, Stanley Nowlan and Howard Heap, published a book outlining the principles of reliability-centered maintenance, a concept still used by manufacturers today to prevent equipment failure.
The book describes two types of equipment failure:
1. Functional failure
Functional failure is the inability of a piece of equipment to perform a specific task or meet a performance standard, such as the failure of a braking system to stop a vehicle on time.
2. Potential failure
Potential failure is a physical condition that indicates functional failure is imminent, such as worn-out brake pads.
The book argues that while scheduled preventive maintenance based on prescribed recommendations can help avoid equipment failures, the approach is insufficient for the most complex equipment. It can also be inefficient because you're often performing routine maintenance or replacements when it isn’t necessary.
That’s why it’s important for manufacturers to take a more holistic look at the equipment’s entire system (including all components), as well as how often it’s used, its environment, and the amount of stress it is withstanding.
Using the reliability-centered maintenance model, you can more accurately predict when equipment may fail.
How can condition-based maintenance prevent equipment failure?
For manufacturing plants, preventive maintenance should be a given. Unfortunately, the Vanson Bourne Research study found 70% of companies don’t know when assets are due for maintenance or upgrades. With no effective guidance in place, your technicians are reactive instead of proactive. They frequently overlook guidelines for repairs or replacement of parts, responding only to the complete failures or potential failures they can see.
As important as it is to have a comprehensive preventive maintenance plan, for companies with complex equipment, it’s not enough.
Industrial manufacturing experts estimate only 20% of failures are related to equipment age, while the rest are due to other factors—including degradation.
This degradation manifests itself in many ways, including changes in temperature, vibration, or noise levels.
Condition-based monitoring (CBM) uses diagnostic testing to identify these signs of impending equipment failure before they lead to outages.
Also known as predictive maintenance, CBM involves tracking condition metrics that trigger automatic work orders.
For example, if you want to ensure your engine isn’t overheating—which could indicate a faulty cooling system—you can assign someone to inspect it when the temperature rises above a certain level.
How can enterprise asset management software help?
Given the shocking costs of equipment failure, you can’t afford not to be proactive about equipment maintenance.
Our enterprise asset management software helps you implement and elevate your preventive maintenance program with condition-based monitoring.
You can use our inspections module for diagnostic testing and automatically trigger a maintenance workflow when a variable (like temperature) is out of range.
You can also see full visibility into every piece of equipment, including:
- Operating hours
- Total lifetime costs
- Maintenance history
- Parts replaced
- Owner’s manuals
This gives you more insight into when equipment failure is likely, based on its age, how often it has been used, and what previous issues have occurred.
If you’re considering a total replacement due to repeated failures, having this data at your fingertips makes it easier to determine whether it’s worth the investment.
And, with the ManagerPlus Lightning mobile app, your team can access this information from anywhere. Ready to elevate your maintenance program and prevent equipment failure? Schedule a demo today.
About the author
ManagerPlus is the preferred solution across the most asset-intensive industries, including Fortune 500 companies, to improve reliability and minimize downtime.