CQPA cheat sheet

CQPA is a certification administered by the ASQ; the body of knowledge is organized around quality fundamentals, data management, process analysis, and improvement methods rather than a single enumerated list of weighted domains.

Core statistical toolkit: measures of central tendency (mean, median, mode), dispersion (range, variance, standard deviation), and position (percentile, quartile, z-score); z = (x − μ)/σ.

Control chart selection rule: variables data (X̄-R, X̄-s, individuals) for measurable characteristics; attributes data (p, np, c, u) for count or proportion characteristics.

Process capability: Cp = (USL − LSL)/6σ measures potential capability; Cpk = min[(USL − μ)/3σ, (μ − LSL)/3σ] measures actual capability and penalizes off-centering.

Sampling: acceptance sampling uses AQL, LTPD, and OC curves; random sampling reduces bias; sample size drives the width of confidence intervals and the power of tests.

Measurement system analysis: repeatability is equipment variation (within-operator), reproducibility is appraiser variation (between-operators); gauge R&R typically targets under 10% of tolerance or process variation.

PDCA (Plan-Do-Check-Act) and DMAIC (Define-Measure-Analyze-Improve-Control) are the two dominant improvement frameworks; DMAIC is the Six Sigma structure for existing processes.

Seven basic quality tools: check sheet, histogram, Pareto chart, cause-and-effect diagram, scatter diagram, control chart, and flowchart; Pareto applies the 80/20 prioritization principle.

Cost of quality categories: prevention, appraisal, internal failure, external failure; failure costs are generally the largest and most reducible category.

Probability basics: mutually exclusive events P(A or B) = P(A) + P(B); independent events P(A and B) = P(A)·P(B); complement rule P(A') = 1 − P(A).

Normal distribution: approximately 68% of values fall within ±1σ, 95% within ±2σ, and 99.7% within ±3σ of the mean; standardized value z = (x − μ)/σ.

Hypothesis testing: the null hypothesis assumes no difference; the p-value is the probability of observing the result (or more extreme) if the null is true; reject H0 when p < α.

Type I error (α) is rejecting a true null hypothesis; Type II error (β) is failing to reject a false null; power = 1 − β.

Confidence interval for a mean (known σ): x̄ ± z(α/2)·σ/√n; increasing n narrows the interval by a factor of √n.

Correlation coefficient r ranges from −1 to +1; r measures linear association only and does not establish causation.

Regression: y = a + bx, where b is the slope (change in y per unit change in x); R² is the proportion of variation in y explained by the model.

Data types: nominal (labels), ordinal (ranked), interval (equal spacing, no true zero), and ratio (equal spacing with a true zero); the data type determines which statistical test is valid.

ANOVA tests equality of means across three or more groups; it compares between-group variation to within-group variation via the F statistic.

Process mapping: SIPOC (Suppliers, Inputs, Process, Outputs, Customers) frames process scope; flowcharts reveal decision points, loops, and handoffs.

Value stream mapping distinguishes value-added from non-value-added steps; the ratio of value-added time to total lead time is the process cycle efficiency.

FMEA: Risk Priority Number RPN = Severity × Occurrence × Detection; higher RPN indicates higher priority for corrective action.

Root cause analysis: the 5 Whys drills to a cause; the cause-and-effect (Ishikawa) diagram organizes causes into categories such as Man, Machine, Material, Method, Measurement, and Environment.

Control chart rules: a point beyond control limits signals special cause; runs of 7 or more points on one side of the centerline or trends of 6+ points also signal nonrandom behavior.

Process capability indices require a stable, in-control process before interpretation; a capable process has Cpk of at least 1.33 in many manufacturing settings.

Pareto analysis: a small number of causes (roughly 20%) typically produce most of the effects (roughly 80%); prioritize the tallest bars first.

Lean waste categories (TIMWOOD): Transportation, Inventory, Motion, Waiting, Overproduction, Overprocessing, and Defects.

Kaizen is continuous incremental improvement; kaizen events are focused, time-boxed improvement workshops.

5S workplace organization: Sort, Set in order, Shine, Standardize, Sustain.

Poka-yoke is error-proofing that prevents defects at the source rather than detecting them after the fact.

SPC implementation sequence: select the characteristic, choose the chart type, establish control limits from a stable baseline, monitor, and react to out-of-control signals.

Control plan documents the process controls, monitoring frequency, and reaction plan for each significant characteristic.

Quality audits verify conformance to planned arrangements; corrective action addresses root cause, while containment addresses the immediate symptom.

Benchmarking compares performance against best-in-class internal or external processes to set improvement targets.