Reliability Data Analysis and Statistics Flashcards
7 cards from real CMRP practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 Reliability Data Analysis and Statistics flashcards as text
What are the two primary parameters of a two-parameter Weibull distribution?
Answer: Shape (β) and scale (η)
The two-parameter Weibull distribution uses the shape parameter (β) and scale parameter (η, characteristic life) to model failure behavior across a wide range of failure types.
In Weibull analysis, what does a shape parameter (β) value of less than 1 indicate about the failure pattern?
Answer: Infant mortality failures with a decreasing failure rate
β < 1 indicates a decreasing failure rate, characteristic of infant mortality where weak items fail early and the surviving population becomes more reliable over time.
When the Weibull shape parameter (β) equals exactly 1, the Weibull distribution reduces to which distribution?
Answer: Exponential distribution
β = 1 produces a constant failure rate, which is the defining characteristic of the exponential distribution used for random, memoryless failures.
What does the eta (η) parameter represent in a Weibull distribution?
Answer: The characteristic life at which 63.2% of units have failed
The scale parameter η (characteristic life) is the time at which exactly 63.2% of units have failed, regardless of the value of the shape parameter β.
A Weibull shape parameter (β) of approximately 3.5 is often associated with which type of failures?
Answer: Wear-out failures approximating a normal distribution
β ≈ 3.5 produces a symmetrical, bell-shaped failure distribution that closely approximates the normal distribution, typically seen in mechanical wear-out and fatigue failures.
Which graphical technique is most commonly used to estimate Weibull parameters from failure data?
Answer: Weibull probability paper with median rank plotting
Median rank plotting on Weibull probability paper (or software equivalent) linearizes the Weibull CDF so that slope and intercept yield the shape and scale parameters.
The lognormal distribution is best suited to model which reliability scenario?
Answer: Repair times and failures due to fatigue or corrosion crack growth
The lognormal distribution is commonly applied to repair times and cumulative-damage failure mechanisms such as fatigue, corrosion, and stress-corrosion cracking.