Assessment Flashcards
7 cards from real Certified Six Sigma Black Belt Exam practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 Assessment flashcards as text
A Gauge R&R study reveals that %Study Variation for repeatability is 28% and for reproducibility is 19%. What is the overall assessment of this measurement system?
Answer: Marginal — total variation exceeds 30% and requires investigation
When combined %Study Variation (repeatability + reproducibility) exceeds 30%, the measurement system is considered marginal to unacceptable and warrants improvement.
Which metric best quantifies the ability of a process to meet customer specifications over the long term, accounting for process shifts?
Answer: Ppk
Ppk uses overall (long-term) standard deviation and accounts for process centering, making it the best long-term capability index.
During an assessment of a transactional process, a team finds a defect rate of 3,400 DPMO. What sigma level does this correspond to?
Answer: 4.0 sigma
A DPMO of 3,400 corresponds to approximately 4.0 sigma (short-term), accounting for the standard 1.5 sigma shift.
A Black Belt is assessing process stability before calculating capability indices. Which tool is most appropriate for this evaluation?
Answer: Control chart
Control charts reveal whether a process is in statistical control (stable) over time, which is a prerequisite for valid capability calculations.
In a process assessment, the number of defects per unit (DPU) is 0.08. Assuming a Poisson distribution, what is the approximate first-pass yield (FPY)?
Answer: 92.3%
FPY = e^(−DPU) = e^(−0.08) ≈ 0.923, or approximately 92.3%.
A team is assessing which of five potential root causes contributes most to output variation. Which statistical technique should they use?
Answer: Multi-vari analysis
Multi-vari analysis is specifically designed to identify and compare sources of variation across families (positional, cyclical, temporal) to find dominant contributors.
When assessing process capability for a non-normal distribution, what is the most rigorous approach?
Answer: Apply a Box-Cox transformation or fit an appropriate distribution
Transforming non-normal data (Box-Cox) or fitting the actual distribution ensures capability indices accurately reflect the true process performance.