Applying Weibull for Maximum Likelihood Estimation to Left-Truncated and Right-Censored Lifetime Data
This white paper presents a rigorous statistical methodology for analyzing transmission line asset reliability using Weibull distribution analysis. The approach specifically addresses the analytical challenges inherent in utility asset data: left-truncated observations from legacy system migrations and informatively right-censored data from inspection-driven replacement programs.
A study of approximately 15,000 transmission structures across an 11,000-kilometer network demonstrates the Weibull methodology’s practical application. By employing Maximum Likelihood Estimation (MLE) rather than ordinary least squares regression, the analysis produces unbiased parameter estimates even under complex censoring conditions that would render traditional approaches unreliable.
Key findings reveal that unique classification of assets exhibit similar but different reliability characteristics, with characteristic lives (η) of 60 and 75 years, respectively, and shape parameters (β) indicating wear-out failure modes in both populations.