The Hazard Function, often referred to as the failure rate λ(t)\lambda(t), is a fundamental metric in reliability engineering. It represents the instantaneous probability of failure at time tt, given that the component has survived until that time. For most physical assets, this function follows the iconic "Bathtub Curve".

Phase I: Infant Mortality

Early-life failures caused by manufacturing defects or installation errors. Characterized by a decreasing failure rate.

Phase II: Useful Life

Failure occurs randomly due to unpredictable external stresses. Characterized by a constant failure rate (Exponential distribution).

Phase III: Wear-out

Failures caused by physical fatigue, corrosion, or material degradation. Characterized by an increasing failure rate.

Interactive Bathtub Modeler

Adjust the parameters below to witness how different failure distributions affect the overall reliability profile of your system over time.

Model Parameters

Phase I: Infant Mortality
Phase II: Useful Life
Phase III: Wear-out

Adjust the failure rates to simulate different asset types (e.g., Electronics vs. Mechanical parts).

Instantaneous Failure Rate λ(t)

Reliability Function R(t)

Survival Probability (%)

The Weibull Connection

Reliability engineers often use the Weibull Distribution to model these phases numerically. By adjusting the shape parameter (kk or β\beta):

  • k<1k < 1: Models Phase I (Decreasing failure rate).
  • k=1k = 1: Models Phase II (Constant failure rate - memoryless property).
  • k>1k > 1: Models Phase III (Increasing failure rate).

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Technical Standards & References

REF [1]
Hoang Pham (2021)
Statistical Reliability Engineering
In-depth analysis of failure rate functions and hazard models.
REF [2]
Marvin Rausand (2004)
Reliability Engineering: Methods and Applications
Traditional bathtub curve derivation and Weibull modeling foundations.
Mathematical models derived from standard engineering protocols. Not for human safety critical systems without redundant validation.

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