R Programming Language Certification Quality Control & Assurance 3 — Questions and Answers
Question 1: In R, which control chart type is most appropriate for monitoring the proportion of nonconforming items in variable-sized subgroups?
- np chart
- p chart (Correct answer)
- c chart
- u chart
Correct answer: p chart
The p chart monitors the proportion of nonconforming items and accommodates variable subgroup sizes, unlike the np chart which requires fixed subgroup sizes.
Question 2: When running `gage.rr()` in R's `SixSigma` package, a %Contribution of measurement system above what threshold is generally considered unacceptable?
- 10%
- 30% (Correct answer)
- 50%
- 5%
Correct answer: 30%
A measurement system %Contribution (or %Study Variation) above 30% is generally unacceptable; below 10% is acceptable; 10–30% may be acceptable depending on context.
Question 3: Which R function from the `qcc` package generates a Pareto chart for quality defect analysis?
- pareto.chart() (Correct answer)
- paretoPlot()
- pareto()
- quality.pareto()
Correct answer: pareto.chart()
`pareto.chart()` in the `qcc` package creates a Pareto chart showing defect categories sorted by frequency with a cumulative percentage line.
Question 4: In R, what is the primary purpose of Western Electric (WECO) rules applied via `qcc`?
- To detect non-random patterns beyond just points outside control limits (Correct answer)
- To calculate control limits using 2-sigma instead of 3-sigma bounds
- To normalize non-Gaussian process data before charting
- To set the AQL for acceptance sampling plans
Correct answer: To detect non-random patterns beyond just points outside control limits
WECO rules detect non-random patterns (runs, trends, stratification) within control limits that a single 3-sigma rule alone would miss.
Question 5: In the context of R-based SPC, what does 'Phase I' analysis refer to?
- Retrospective analysis to establish baseline control limits from historical data (Correct answer)
- Real-time monitoring of live production data
- Acceptance sampling of incoming materials
- Capability analysis after process stabilization
Correct answer: Retrospective analysis to establish baseline control limits from historical data
Phase I SPC involves retrospective analysis of historical data to estimate process parameters and establish control limits for future Phase II monitoring.
Question 6: Which R command correctly creates a c-chart for monitoring the number of defects per inspection unit?
- qcc(data, type='c') (Correct answer)
- qcc(data, type='np')
- qcc(data, type='u')
- qcc(data, type='xbar')
Correct answer: qcc(data, type='c')
Using `type='c'` in `qcc()` creates a c-chart appropriate for count data where each unit is inspected for multiple possible defects.
Question 7: What R package provides functions for Measurement System Analysis (MSA) including linearity and bias studies?
- SixSigma (Correct answer)
- qcc
- qualityTools
- MeasurementSystems
Correct answer: SixSigma
The `SixSigma` package includes functions like `ss.lsa()` for linearity and stability analysis and `ss.rr()` for gauge R&R studies.
R Programming Language Certification Quality Control & Assurance 3
In R, which control chart type is most appropriate for monitoring the proportion of nonconforming items in variable-sized subgroups?