Life Data Analysis Flashcards

In accelerated life testing (ALT) data analysis, the Arrhenius model relates failure acceleration to:

Answer: Temperature in Kelvin

The Arrhenius model uses absolute temperature (Kelvin) and an activation energy to model thermally-driven acceleration of failure rates.

A Weibull probability plot shows data points curving upward (concave up) rather than forming a straight line. This most likely indicates:

Answer: A mixed population or two failure modes

Upward curvature on a Weibull plot often signals a mixed (competing) failure mode population, where two distinct subpopulations are present.

The B10 life of a component refers to the time by which:

Answer: 10% of units have failed

BX life (here B10) is the time at which X% of the population has failed, so B10 is the 10th-percentile failure time.

Maximum Likelihood Estimation (MLE) is preferred over rank regression for life data analysis primarily because:

Answer: It handles censored data more rigorously and is asymptotically efficient

MLE properly incorporates censored observations into the likelihood function and achieves the Cramér-Rao lower bound efficiency for large samples.

For a 3-parameter Weibull distribution, the third parameter γ (gamma) represents:

Answer: A guaranteed failure-free (location) period

The location parameter γ shifts the distribution so that no failures can occur before time γ, representing a failure-free period.

When computing failure rates from field warranty data, a major challenge compared to controlled test data is:

Answer: Exact time-in-service for all units is typically unknown

Warranty data rarely includes precise in-service hours for non-failed units, making suspension times uncertain and requiring special analysis methods.

The hazard function h(t) for an exponential distribution with failure rate λ is:

Answer: λ

The exponential distribution has a constant hazard rate h(t) = λ for all t, reflecting the memoryless property.