Weibull Analysis for Failure Prediction

What is Weibull Analysis?

Weibull Analysis is a powerful statistical method used in reliability engineering to model time-to-failure data. It is highly versatile and can model the failure characteristics of complex systems, from infant mortality to wear-out failures.

The analysis yields two key parameters:

• Beta (β) - The Shape Parameter: Describes the failure mode.
  • β < 1: Decreasing failure rate (infant mortality). Failures are more likely at the beginning.
  • β = 1: Constant failure rate (random failures). The process follows an exponential distribution.
  • β > 1: Increasing failure rate (wear-out). Failures become more likely as the product ages.
• Eta (η) - The Scale Parameter: Also known as the characteristic life. It's the time at which 63.2% of the population is expected to have failed.

Why is Weibull Analysis Useful?

Originally developed by Waloddi Weibull to model material strength, this analysis is now a cornerstone of modern reliability engineering. It allows engineers and managers to make data-driven decisions about:

• Maintenance Planning: Predict when parts are likely to fail to schedule preventive maintenance.
• Warranty Analysis: Forecast warranty claims and costs.
• Design Improvement: Identify failure modes (e.g., wear-out vs. early failures) to guide product improvements.
• Risk Assessment: Quantify the reliability of a component or system over its operational life.

How to Use This Tool

1. Enter Failure Data: In the first field, type the times at which failures occurred, separated by commas. These can be hours, cycles, kilometers, etc. You can also press "Load Example" to see a sample dataset.
2. Analyze: Press the "Analyze Failures" button.
3. Review Results:
   • Numerical Results: Review the calculated Beta (β), Eta (η), and Mean Time To Failure (MTTF). Interpret the Beta value to understand the failure mode of your system.
   • Weibull Probability Plot: This special chart visualizes your failure data. If the points form a reasonably straight line, it confirms that the Weibull distribution is a good fit for your data. The blue line is the best-fit regression line used to calculate the parameters.
   • Make a Prediction (Optional): Enter a specific time (in the same units as your failure data) into the prediction field and press "Analyze Failures" again to see the cumulative probability of failure by that time.
   • Add and Export: You can add multiple analyses to a list and then export all results to an Excel file for your reports.