If you had to bet money on when an asset would fail, would you put it closer to the beginning or the end of the life cycle? Most people would guess the end, but the beginning is an equally safe bet. 

It feels counterintuitive, but it all makes perfect sense once you understand the bathtub curve.

What is the bathtub curve?

The bathtub curve is a graph that represents the failure rate of an asset over time. It is used as a very basic measure to help understand why failures occur on certain assets and how to predict and prevent them. It is called the “bathtub curve” because it resembles the cross-section of a bathtub: steep sides with a flat bottom.

What are the three phases of the bathtub curve?

The bathtub curve is characterized by three parts:

  • Infant mortality period
  • Normal life period
  • Wear out period


Infant mortality period

The infant mortality period can also be known as the early failure period and occurs at the very beginning of an asset’s lifecycle the moment you install and begin using the asset. It’s important to remember that this doesn’t begin the moment you acquire it, just the moment you install it and begin using it. For example, if you purchase an asset and it sits in your warehouse for six months while you finish building your new facility, those six months are not counted in the bathtub curve because you haven’t begun using it yet.

The reason it’s called the infant mortality period is that there tends to be a high rate of failures during this short amount of time. This is during the very beginning of the asset’s lifecycle where failures are most often a result of manufacturer defects, incorrect installation, or improper usage as operators either received improper training or are learning how to use the asset.

Discovering failures during this period can be helpful as you can discover defects that can be replaced under manufacturer warranty. It also helps to discover other human errors in the asset lifecycle so they can be corrected to prevent future failures.

Normal life period

During the normal life or constant failure rate period, an asset maintains a relatively constant failure rate. In this period, manufacturer defects and improper usage are far less common and most of the failures are caused by normal wear and usage of the asset. The rate of these failures over time typically maintains a constant ratio.

Basically, if an asset’s normal life period is 10 years, if you make six repairs in the first three years, then only four repairs in the last seven years, over the normal life period, those repairs average out to be a constant failure rate.

There are two main reasons that the failure rate appears constant: 1) some of the failures are truly random due to external environmental factors or simply chance occurrences, 2) there are so many different failures and failure modes contributing to the formula that the overall rate appears to be random.

While some of these failure modes truly are random, the good news is that most of them can be accurately predicted and repaired before they become true failures with the help of a preventive maintenance (PM) program.

A good example is a work truck. You know that the tires on the truck will wear out after a set number of miles, and if you know how many miles the truck drives over a set period of time, you can accurately predict when the tires will fail and can change them before that happens. What you can’t predict, however, is driving over a nail and puncturing a tire while on the road.


Wear out period

Also known as the end-of-life period, this period is the final stage of the life cycle of your assets where failures occur due to assets and parts reaching the end of their designed useful life. These end-of-life failures are generally predictable and are often even specified in the manufacturer’s documentation about the asset. During this period, the failure rates increase sharply resulting in the other side of the bathtub on the curve.

Depending on the asset, sometimes the parts that are designed to reach this wear-out period can be replaced entirely to reset the curve. This doesn’t apply to every asset and there are still other components of the asset that will need to be considered, but sometimes performing these repairs can significantly increase the lifecycle of an asset.

What is MTBF and how does it apply to the bathtub curve?

Mean time between failures (MTBF) is used to determine the average amount of time between failures that can be repaired for an asset. This is used generally for larger assets where a failure does not result in the entire asset needing to be replaced.

Think of a machine press in a manufacturing facility. Many parts of the machine can be replaced quickly and inexpensively without having to replace the machine itself.

So let’s say you wanted to know what the MTBF was for one of your machines over the past year. You would divide the total number of hours, or miles for vehicles, that the machine operated by the number of failures that needed maintenance work.

Number of operational hours/miles / Number of failures = MTBF

60,000 hours / 4 failures = 6000 hours

This essentially means that you’re getting about 6,000 hours of full run-time from that machine without having to perform any repairs.

Calculating the MTBF is most useful during the normal life period of the bathtub curve to help you accurately predict when failures might occur for your assets.

How can EAM software help extend the asset life cycle?

When assets move from the infant mortality period into the normal life period, the task then becomes to avoid as many failures as possible to keep the asset running and operating as expected for as long as you can.

Preventive maintenance is the most efficient and cost-effective way to maintain assets over the long term and extend their useful life. Preventive maintenance is all about gathering as much data s you can on your assets, then tracking their usage and making repairs before known failure points.

Enterprise asset management (EAM) software is the tool that helps you develop, implement, and operate an effective preventive maintenance program. With it, you can input all the necessary data about your asset as soon as you install it and tell the software to automatically generate and assign work orders to your technicians when it’s time for repairs.

One of the most important benefits of EAM software is that all of the data from your preventive maintenance program is tracked and stored over time so you can generate detailed cost-analysis reports to see how effective your program is and where you have room for improvement.

You can also track your asset performance over time to see when it’s beginning to reach the wear-out period and develop a plan to repair or replace it.


Executive summary

The bathtub curve is a graphical representation of the expected failure rates of assets. It is comprised of three parts:

  • Infant mortality period – characterized by a high rate of failures in a short amount of time
  • Normal life period – the number of failures over time remains constant
  • Wear out period – failures again occur at a high rate as the asset reaches the end of the lifecycle

The normal life period is where the most impact can be had on the overall useful life of the asset. A strong preventive maintenance program where enterprise asset management (EAM) software is used to track asset performance and predict equipment failures is proven to extend the useful life of an asset.

Next steps

If you’re ready to see how EAM software can help extend the life of your assets, reach out to our experts to schedule a personalized, one-on-one demo to see for yourself how effective it can be.

About the author

Jason Cockerham

Jason is a storyteller at heart with a career spanning everything from film and TV to iPhones. Just don't expect much before his first cup of coffee.
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