Lean Six Sigma Black Belt Statistical Process Control (SPC) 1 Flashcards
6 cards from real Lean Six Sigma Black Belt Certification practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 6 Lean Six Sigma Black Belt Statistical Process Control (SPC) 1 flashcards as text
An Individuals and Moving Range (I-MR) chart is the appropriate control chart choice when:
Answer: Each inspection yields only a single observation and subgrouping is not feasible
I-MR charts are designed for situations where only one measurement is produced per time period or rational subgrouping is impractical (e.g., slow processes, destructive testing, or homogeneous batches). The Moving Range between consecutive individuals estimates short-term variation in place of within-subgroup variation.
When should a U-chart be used instead of a C-chart for monitoring process defects?
Answer: When the inspection area, unit size, or opportunity for defects varies between subgroups
Both C and U charts assume Poisson-distributed count data, but the C-chart requires a constant opportunity area (e.g., fixed unit size). When the inspection unit or sample area varies, defect counts are normalized to a per-unit rate, requiring the U-chart (defects per unit = c/n).
What is the fundamental distinction between Ppk and Cpk process capability indices?
Answer: Ppk is calculated using overall (long-term) standard deviation; Cpk uses within-subgroup (short-term) standard deviation
Cpk uses σ̂ estimated from within-subgroup variation (via R-bar or S-bar), capturing only short-term, common-cause variation. Ppk uses the overall sample standard deviation, which includes both within- and between-subgroup variation. The ratio Cp/Pp (or Cpk/Ppk) reveals how much long-term drift inflates total variability.
Compared to a standard Shewhart X-bar chart, an EWMA (Exponentially Weighted Moving Average) chart offers its greatest advantage when:
Answer: Small, sustained shifts of ±0.5σ to ±1.5σ in the process mean must be detected
Shewhart charts are optimal for detecting large, abrupt shifts but are relatively insensitive to small drifts. The EWMA chart applies exponential weighting to historical data, making it far more sensitive to small, persistent mean shifts. The smoothing parameter λ controls the trade-off between responsiveness and stability.
In Statistical Process Control, a single point plotting beyond the ±3σ control limits should be interpreted as:
Answer: A special-cause signal warranting investigation before the next production run
Control limits are set at ±3σ so that roughly 99.73% of points from a stable process fall within them by chance alone. A point outside these limits has a very low probability (~0.27%) of occurring due to common cause alone, making it a strong signal of a special (assignable) cause that must be investigated and addressed—not a reason to adjust the process arbitrarily.
An NP-chart is preferred over a P-chart for monitoring fraction nonconforming when:
Answer: The subgroup size is constant and plotting the actual count of nonconforming units is more intuitive
Both the P-chart (proportion nonconforming) and NP-chart (number nonconforming) are valid for binomial attribute data. The NP-chart is specifically suited to constant subgroup sizes because it plots the raw count np rather than the proportion p/n, which operators and technicians often find more natural to interpret directly.