Asset health indices are widely used to support maintenance, replacement, and risk-based decisions, but their value depends heavily on the quality, completeness, and interpretation of the data behind them. This column examines why an AHI should not be treated as a single absolute number, especially when input data may be incomplete, outdated, inaccurate, or affected by measurement uncertainty. It discusses the importance of assigning confidence levels to AHI results, supported by subject matter expert review and structured evaluation of available data. The column also considers how statistical approaches, such as Monte Carlo simulation, can help express uncertainty more clearly and support better asset management decisions.
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This column examines why an AHI should not be treated as a single absolute number, especially when data may be incomplete, outdated, inaccurate, or affected by measurement uncertainty.
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