Bathtub Curve (Failure Rate Over Lifecycle)

The bathtub curve describes how failure rates change over a product's lifecycle in three phases. Infant mortality (early life): high failure rates from manufacturing defects, installation errors, and weak components that are weeded out during burn-in or early use. Useful life (middle): low, approximately constant failure rate from random, unpredictable causes. Wear-out (end of life): rising failure rates from fatigue, corrosion, degradation, and accumulated damage. Practitioners use this model to set maintenance strategies: aggressive inspection during infant mortality, condition-based monitoring during useful life, and proactive replacement before wear-out. The curve also informs warranty design — warranties cover infant mortality failures, which are the manufacturer's responsibility.

When to use it

When planning maintenance or support strategies for any system over its lifecycle, when distinguishing between early-life failures and end-of-life degradation, when setting warranty or support periods, or when deciding whether to repair or replace aging components.

How it can help

The bathtub curve applies to any system with a lifecycle. New employees have high 'failure rates' (mistakes, misunderstandings) during onboarding, low rates during productive tenure, and increasing issues as burnout or skill obsolescence sets in. New software releases follow the same pattern — many bugs initially, stability in the middle, increasing fragility as technical debt accumulates. Understanding which lifecycle phase you're in determines whether to focus on screening (infant mortality), monitoring (useful life), or replacement planning (wear-out). Attempting to fix wear-out failures with the same tools that address infant mortality is a common and costly mistake.