Reliability

What is Reliability?

Reliability in facilities management is a key performance indicator (KPI) that measures the likelihood that a system, component, or piece of equipment will work as expected under given conditions within a specified period. Higher reliability generally also demonstrates efficiency, safety, and cost savings.

By maintaining a high reliability metric, facilities can avoid unnecessary downtime and reduce costs associated with unexpected repairs or breakdowns.

Additionally, facilities with higher equipment reliability usually have a better overall reputation. That’s because reliable equipment ensures consistent operations, high-quality products, and dependable service.

How is Reliability Calculated?

The simplest method to determine reliability is to calculate the mean time between failures (MTBF). MTBF is calculated by dividing the total amount of time an asset is running by the number of breakdowns that occurred within the same time frame.

The formula is as follows.

MTBF = Number of Breakdowns/Total Uptime

For example, if a machine has been running for 1000 hours and has experienced 10 breakdowns during this period, the calculation would be:

MTBF = 10 breakdowns/1000 hours = 100 hours

Another way to determine reliability is through the reliability function. The difference between the reliability function and MTBF is that MTBF calculates the average time between failures and the reliability function calculates the probability of failure.

The formula looks like this:

R(t) = e^(-λt)

The symbol 𝜆 stands for the failure rate, which is measured with your MTBF, and t is the time. The 𝑒 represents a mathematical constant known as Euler’s number, which is approximately equal to 2.71828. It’s used here because it helps describe how things change continuously over time.

In this particular reliability testing situation, the failure rate (λ) is multiplied by the time (t) you are considering. When you place this product in the exponent of Euler’s number (e), e^(-λt) models the decay of reliability over time.

Returning to the earlier example of a machine that experienced 10 breakdowns over 1000 hours, the reliability function would go as follows. λ provides the same result as MTBF

Now, let’s calculate the R(t) of this machine for 500 hours of operation.

• R(500) =e −(1000/1 × 500)
• R(500) =e −0.5

Euler’s number (e) raised to the power of -0.5 gives us:

R(500) = 0.606

This result means there is about a 60.6% chance that the machine will operate without failing over the next 500 hours. What percentage is considered reliable depends on the criticality of the equipment in question.

The higher the percentage, the better the measure of the reliability. This calculation will not account for a breakdown that may occur due to a random error, as that’s impossible to truly predict.

Practical Examples of How Reliability is Used

There are a few ways that a facility manager could use their reliability metric. Here are some examples of how reliability data can be leveraged in a facility.

Maintenance Planning

Facility managers use reliability metrics to schedule maintenance more effectively. This approach helps prevent unexpected equipment failures by planning maintenance based on the likelihood that failure may occur. As a result, maintenance work remains consistent without over-exhausting available resources.

Design and Development

Engineers may leverage reliability data into their designs to build more durable systems. This data guides them in enhancing product resilience, accuracy, and consistency. That’s because measuring reliability can help predict potential failures so engineers can design systems to avoid them.

Risk Management

In industries where failure has significant consequences, like aerospace and healthcare, the pressure to maintain consistent reliability is high. These sectors rely on reliability metrics to manage risks effectively.

Performance Benchmarking

Facilities can compare their reliability metrics with industry standards to pinpoint improvement areas. For example, hospitals may use this data to proactively manage crucial equipment maintenance based on industry requirements. This strategy minimizes the risk of costly and dangerous failures.

Ways to Improve Reliability

Improving reliability involves enhancing the overall performance and lifespan of equipment. Some key methods to help your facility achieve this goal include the following.

Regular Preventive Maintenance

Regular preventive maintenance helps ensure that equipment operates smoothly and reduces the likelihood of unexpected breakdowns. This proactive approach greatly extends the lifespan and enhances the performance of equipment.

Quality Parts and Materials

Utilizing high-quality, durable parts in equipment can significantly improve its reliability. These parts are better equipped to withstand wear and tear, leading to fewer failures and longer operational life. Higher-quality parts also have the ability to last longer, so you’ll require fewer replacements.

Redundancy

Adding redundant systems that can produce the same results consistently. Having this internal reliability provides a backup that can operate if the primary system fails. This method is particularly vital in critical operations where system failures can lead to severe consequences.

Predictive Maintenance

Predictive maintenance involves using advanced monitoring tools to predict equipment failures before they happen. Using this strategy allows for timely interventions that can prevent costly downtime and repairs.

Design for Reliability

Designing for reliability is a strategic way to enhance system functionality from the outset. This approach focuses on creating equipment that is less likely to fail and easier to maintain.

Operator Training

Proper operator training will prevent errors that can cause equipment wear or failure. Well-trained operators can handle equipment more effectively, which will maintain its reliability. For instance, airlines can enhance aircraft reliability by training maintenance crews in best practices, not just by using more reliable components.