Failure Rate

What is Failure Rate?

Failure rate (or hazard rate) is a metric used in Facilities Management Services to quantify the frequency at which an asset, component, or system fails during normal operation. It’s typically expressed as a rate per unit of time, indicating how often failures occur within a specified period. This metric is crucial for understanding the reliability and performance of facility assets and for making informed maintenance and replacement decisions. A high failure rate suggests a need for immediate attention and potential improvements, while a decreasing failure rate indicates reliable and well-maintained assets. The total system failure rate measures how likely it is for the entire system to fail over a certain time, helping to plan for and prevent problems.

How is the Failure Rate Calculated?

The failure rate is calculated by dividing the number of failures by the total time under observation. This metric is typically used to assess the reliability of products and systems over a specific period of time. Here’s how you can calculate the failure rate:

Formula:

Failure Rate = Number of Failures / Total Time

Components Explained

1. Number of Failures: This is the total count of failures that have occurred within the specified period.
2. Total Time: This is the sum of the operational time for all units being considered, often expressed in hours, cycles, or similar units depending on the context.

For example, if you have 10 failures over a machine operating for a total of 20,000 hours, the failure rate would be calculated as follows:

Failure Rate = 10 Failures / 20,000 Hours = 0.0005 failures per hour.

This metric is crucial in understanding how often failures occur. Failure rates help plan maintenance, improve designs, and enhance reliability.

Understanding Failure Rate and MTBF

Mean Time Between Failures (MTBF) is a related metric that provides a statistical estimate of the expected time between failures for a system or component. For systems with a constant failure rate, the failure rate is the inverse of MTBF. This means that if a component has an MTBF of 500,000 hours, you can calculate the failure rate as follows for any desired time unit:

• Example Calculation:
  • Desired Time Unit for Failure Rate: 1,000,000 hours
  • MTBF: 500,000 hours
  • Failure Rate = 1,000,000 hours / 500,000 hours = 2 failures per million hours

Application in Real-World Scenarios

1. Existing Products:
   • MTBF is typically derived from historical failure data for products already on the market. This data provides insights into the product’s reliability over its operational life.
2. New Products:
   • For new products or ones that have undergone significant changes, estimating MTBF before any real-world data is available is crucial. This estimation can be based on historical data from similar products, the assumed reliability of new components, or standard reliability prediction methods.
3. Reliability Prediction:
   • If a product’s design changes are not expected to significantly affect reliability, historical failure rates from similar models can be used. However, if the design changes are substantial, reliability predictions will need to be recalculated, often using methods such as reliability block diagrams, fault tree analysis, or parts count analysis.

The Cumulative Distribution Function

The cumulative distribution function (CDF) is key to understanding the reliability of products or systems over time. The CDF helps to describe the probability that a system or component fails by a certain time t, which is a crucial aspect of reliability engineering.

Reliability Function

The reliability function, often denoted as 𝑅(𝑡)R(t), counterparts the CDF of the time until failure. It’s defined as: 𝑅(𝑡)=1−𝐹(𝑡)R(t)=1−F(t) Here, 𝐹(𝑡)F(t) is the CDF of the time until failure, indicating the probability that a failure will occur by time t. 𝑅(𝑡)R(t) represents the probability that the component or system continues to operate without failure up to time t. The reliability function focuses on success, rather than failure.

Relationship to Failure Rate

The connection between functions and failure rate is important. The failure rate assesses how often failures happen within a short time after a given moment, assuming nothing has gone wrong up to that point. It helps predict when things might go wrong, which is crucial for planning maintenance, setting warranty periods, and managing risks in product design and use. This way, companies can better prepare for potential issues and ensure their products are as reliable as possible.

How Failure Rate is Used: Practical examples

The failure rate is used in a variety of ways within Facilities Management Services:

• Maintenance Planning: Understanding the failure rate of equipment helps facility managers plan and schedule preventive maintenance to mitigate risks.
• Risk Assessment: Failure rate data can be used to assess the risk associated with different assets, prioritizing those with higher inspection and replacement rates.
• Performance Monitoring: Tracking the failure rate of newly installed systems or after implementing changes can indicate the success of those initiatives.
• Resource Allocation: The failure rate informs how resources, including budget and personnel, should be allocated to manage asset reliability effectively.

For instance, a facility manager might use failure rate data to determine the reliability of HVAC units across a commercial property portfolio. If certain models show a higher failure rate, they might be targeted for early replacement or more frequent maintenance checks.

Ways to Reduce Failure Rate

Reducing failure rates is a common objective for facility managers seeking to enhance asset and system reliability and performance. Here are several strategies to achieve this:

• Regular Maintenance: Implementing a regular maintenance schedule can prevent failures by addressing wear and tear before it leads to breakdowns.
• Quality Parts: Using high-quality, durable parts for repairs and replacements can reduce the likelihood that a failure occurs.
• Upgraded Design: Redesigning or upgrading systems to eliminate known failure points can decrease the overall failure distribution rate.
• Staff Training: Ensuring that all maintenance staff are adequately trained on the latest techniques and best practices can lead to more reliable asset performance.
• Root Cause Analysis: Analyzing the causes of failures and addressing the underlying issues of such factors can prevent future occurrences and reduce the failure rate.

An example of reducing the failure rate could be a facility conducting a root cause analysis on frequent elevator malfunctions. By identifying and addressing the specific components that are failing, such as worn cables or electrical issues, the facility can implement targeted solutions to reduce the failure rate and improve elevator reliability.

By focusing on these strategies, facilities management can improve the reliability of their assets, extend their lifespan, and optimize operational efficiency, leading to cost savings and enhanced service quality.