Process Variation & Capability Flashcards
7 cards from real SPC practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 Process Variation & Capability flashcards as text
A short-term capability study is best described as measuring variation:
Answer: Within a brief window capturing mainly within-subgroup variation
Short-term capability (Cp/Cpk) is measured over a brief period to capture within-subgroup variation, minimizing between-subgroup sources.
When calculating the estimated process standard deviation using the average range method, which constant is used?
Answer: d2
The constant d2 is used to convert the average range (R-bar) to an estimate of the process standard deviation: σ̂ = R̄/d2.
A process with Cp = 1.5 but Cpk = 0.9 most likely has which characteristic?
Answer: Low process variation but the mean is significantly off-center
When Cp is high but Cpk is low, the process spread is narrow but the mean is shifted away from the target, reducing one-sided capability.
Which of the following is a Western Electric run rule for detecting special causes?
Answer: Two out of three consecutive points beyond 2-sigma on the same side
Two out of three consecutive points in Zone A (beyond 2σ) on the same side is a standard Western Electric run rule signaling a special cause.
In a unilateral tolerance scenario (only one specification limit), which capability index is most appropriate?
Answer: Cpk
Cpk is appropriate for unilateral tolerances because it measures the distance to the relevant single specification limit.
What effect does reducing subgroup size have on an X-bar chart's sensitivity to process shifts?
Answer: Decreases sensitivity to small shifts
Smaller subgroups widen control limits (higher variation in X-bar), reducing the chart's ability to detect small process mean shifts.
The Cpm index (Taguchi capability index) incorporates which additional factor compared to Cp?
Answer: The deviation of the process mean from the nominal target
Cpm penalizes processes whose mean deviates from the nominal target, even if the mean is within specification limits.