Control Chart vs Run Chart: When the Median Line Is Enough and When You Need Control Limits
Control chart vs run chart: median line versus 3-sigma control limits, how many data points each needs, and which to use at each project stage.
Cp vs Cpk: Why Your Process Can Be Capable on Paper and Still Make Scrap
Cp shows potential capability, Cpk shows what you actually make. The gap reveals off-centering you can fix for free, with a worked example and verdict.
X-bar R vs X-bar S Chart: Picking the Right Variation Estimator for Your Subgroup Size
X-bar R or X-bar S chart? The deciding input is subgroup size. Why the range loses efficiency as n grows, with a worked example and a verdict by role.
c-Chart vs u-Chart: Picking the Right Attribute Chart for Defect Counts
c-chart vs u-chart: when each attribute chart fits, constant vs variable inspection units, 3-sigma Poisson control limits, and a clear verdict.
EWMA vs CUSUM Charts: Choosing a Small-Shift Detection Method When Shewhart Isn't Enough
EWMA vs CUSUM control charts: how each detects small process shifts Shewhart misses, ARL comparison, design parameters, and which to pick.
Statistical Process Control vs Inspection: Shifting Quality From Detection to Prevention
Statistical process control vs inspection: where prevention beats detection, where 100% inspection still wins, and how to choose by what you make.
Sample Size for Process Capability Studies: Minimum Requirements for Reliable Cpk
Sample size for process capability studies: the Cpk confidence interval formula, AIAG/ISO/Bosch standards, and worked numbers from n=30 to n=200.
Free SPC Software for Quality Engineers: Control Chart Tools Without Enterprise Pricing
Honest taxonomy of free SPC software for quality engineers — trials vs OSS vs browser tools — and which fits which use case without 30-day clocks.
Common Cause vs Special Cause Variation: Reacting Correctly to Control Chart Signals
Reading control chart signals correctly: tell common cause from special cause, map each Nelson rule to a likely cause, and act without tampering.
CUSUM vs Shewhart Charts: Detecting Small Process Shifts That X-bar Charts Miss
CUSUM vs Shewhart charts for small shift detection: 1-sigma shift takes 44 subgroups on Shewhart vs 10 on CUSUM. Decision framework + EWMA middle ground.
Gage R&R Before SPC: AIAG Acceptance Thresholds, Worked Example, and 5 Fixes When It Fails
Gage R&R workflow with AIAG %GRR thresholds (10/30%) and ndc criterion. Worked example computes %GRR = 30.5% and ndc = 4, plus what to do when MSA fails.
Histograms with Specification Limits: 7 Patterns That Tell You What Cpk Cannot
7 histogram patterns with spec limits and what they mean for process capability: centered, wide, off-center, bimodal, truncated, skewed, non-normal.
p-Chart Control Limits: Variable Sample Size, 3-Sigma Formulas, and Laney p-Prime
Step-by-step calculation of p-chart control limits with a worked PCB inspection example. Covers the variable sample size problem (exact, average-n, and standardized approaches), the np>=5 minimum, and the Laney p-prime chart for overdispersion.
Individual and Moving Range Charts: When Subgroups Are Not Practical
When and how to use the I-MR (Individual Moving Range) control chart. Covers the five scenarios requiring individual charts, a complete worked example with control limit formulas (d2=1.128, D4=3.267), normality assumptions, and sensitivity comparison vs. X-bar R.
Choosing the Right Control Chart: X-bar R, IMR, p, np, c, u Decision Guide
Decision tree for selecting the correct SPC control chart type. Covers variable vs. attribute data, subgroup size thresholds, p-chart and c-chart distribution requirements, CUSUM and EWMA alternatives, and common chart-type mismatches with real consequences.
Cpk vs. Ppk: Which Capability Index to Report and Why the Gap Between Them Matters
Comparison of Cpk and Ppk process capability indices with worked example, formulas, and a decision table for which index to report in PPAP submissions, customer audits, and ongoing SPC monitoring. Includes diagnostic use of the Cpk-Ppk gap.
Western Electric Rules and Nelson Rules: Choosing the Right Out-of-Control Tests for Your SPC Program
Decision framework for selecting between Western Electric Rules (4 tests, 1956) and Nelson Rules (8 tests, 1984) on SPC control charts. Covers false alarm rates, pattern recognition examples, and how to map each rule type to your reaction plan.
X-bar and R Chart Construction: Subgroup Size, Control Limits, and Reading Signals
Step-by-step worked example for building an X-bar and R control chart from CNC manufacturing data. Includes A2, D3, D4 constants for n=5, control limit formulas, pattern rule application, and Cpk calculation.