Crusher Bearing Weibull Analysis Workbook

The workbook implements statistical lifetime data analysis grounded in extreme value theory, where the Weibull distribution serves as the primary model for time-to-failure data due to its flexibility in representing increasing (β > 1), decreasing (β < 1), or constant (β ≈ 1) hazard rates—critical for diagnosing wear-out, infant mortality, or random failure modes in crusher bearings. Users input right-censored or complete failure data (e.g., hours-in-service until seizure, flaking, or vibration alarm), and the workbook performs maximum likelihood estimation (MLE) or rank regression (e.g., median rank plotting) to fit the two-parameter Weibull distribution. Built-in diagnostics—including goodness-of-fit tests (Kolmogorov–Smirnov, Anderson–Darling), probability plots, confidence bounds, and bathtub curve interpretation—help validate model appropriateness and identify outliers or mixed failure mechanisms. Advanced features may include comparative analysis across bearing types, lubrication regimes, or operating conditions (e.g., throughput, feed gradation), enabling reliability-centered decision-making for spares optimization, overhaul scheduling, and design feedback loops to OEMs. Integration with CMMS or SCADA data feeds (via Power Query or API connectors) further enhances its role in digital twin–enabled asset management frameworks.