About Spc
Spc is a skill for applying statistical process control to manufacturing and quality data. It helps practitioners select control charts, assess process stability, and calculate capability indices using documented methods and thresholds.
Key features
- 01Control chart selection by data type
- 02X-bar/R and I-MR setup formulas
- 03Western Electric and Nelson signal rules
- 04Cp, Cpk, Pp, and Ppk calculations
- 05Capability study workflow
Use cases
- 01Choose a chart for measurement or defect data
- 02Investigate signals on a control chart
- 03Assess capability against specifications
Install
Copy the command and run it in a terminal.
npx skills add https:/ / github.com/ robdtaylor/ personal-ai-infrastructure --skill spcAfter installing, type/spcin Claude Code to confirm it loaded.
Bundled files
References and scripts installed along with SKILL.md.
CLAUDE.mdreference/capability-indices.mdcontrol-chart-selection.mdout-of-control-rules.mdtemplates/capability-study.mdDetails
From the project READMEStatistical Process Control (SPC)
When to Activate This Skill
- "Set up SPC for [characteristic]"
- "Calculate Cpk for [process]"
- "What control chart should I use?"
- "Is this process in control?"
- "Interpret out-of-control pattern"
- "Conduct capability study"
- "What's the difference between Cp and Cpk?"
Purpose of SPC
SPC uses statistical methods to monitor, control, and improve processes by distinguishing between:
- Common cause variation - Normal, inherent process variation
- Special cause variation - Abnormal, assignable causes requiring action
Why SPC Matters
Without SPC:
- React only when defects occur
- Cannot predict process behavior
- May over-adjust stable processes
- Miss early warning signs
With SPC:
- Detect problems before defects
- Understand process capability
- Make data-driven decisions
- Continuously improve
Workflow Routing
| Trigger | What to do |
|---|---|
| "what control chart should I use for [data]" | Use Control Chart Selection tables (Variable vs Attribute) to pick X-bar/R, X-bar/S, I-MR, p/np/c/u based on data type and subgroup size |
| "set up SPC / calculate control limits for [characteristic]" | Follow Capability Study Process Steps 1-3, then calculate limits via X-bar/R Chart or Individual/Moving Range (I-MR) Chart formulas |
| "is this process in control?" / "interpret this pattern" | Check plotted points against Out-of-Control Rules (Western Electric Rules 1-4 standard; Nelson Rules 5-8 for detailed analysis) |
| "calculate Cpk/Ppk" / "is this process capable?" | Apply Process Capability formulas, compare to Capability Targets (Cpk/Ppk ≥1.33 minimum, ≥1.67 for CC), interpret PPM via the Interpretation table |
| "what's the difference between Cp and Cpk" / "Cpk vs Ppk" | Explain via the Key Difference: Cp/Cpk vs Pp/Ppk table (within-subgroup vs overall variation) |
| "conduct a capability study" | Walk through Capability Study Process Steps 1-5 |
| "is pre-control appropriate here" | Use Pre-Control (Alternative to SPC) criteria and zone rules |
| "generate SPC report/analysis" | Emit using the Output Format template below |
Control Chart Selection
Variable Data Charts (Measurements)
| Chart | Data Type | When to Use |
|---|---|---|
| X-bar/R | Subgroups n=2-9 | Standard variable control chart |
| X-bar/S | Subgroups n≥10 | Large subgroups |
| I-MR | Individual measurements | Low volume, long cycle, destructive test |
Attribute Data Charts (Counts/Categories)
| Chart | Data Type | When to Use |
|---|---|---|
| p chart | Proportion defective | Variable sample size, defective/not |
| np chart | Count of defectives | Fixed sample size, defective/not |
| c chart | Defects per unit | Fixed area/unit, count defects |
| u chart | Defects per unit | Variable area/unit, count defects |
X-bar/R Chart
Setup
| Parameter | Guideline |
|---|---|
| Subgroup size (n) | 3-5 typical, 5 preferred |
| Subgroup frequency | Rational subgrouping - within-subgroup should be homogeneous |
| Minimum data points | 20-25 subgroups before calculating limits |
Control Limit Formulas
X-bar Chart:
UCL = X̄̄ + A₂ × R̄
CL = X̄̄
LCL = X̄̄ - A₂ × R̄
R Chart:
UCL = D₄ × R̄
CL = R̄
LCL = D₃ × R̄
Constants (A₂, D₃, D₄)
| n | A₂ | D₃ | D₄ |
|---|---|---|---|
| 2 | 1.880 | 0 | 3.267 |
| 3 | 1.023 | 0 | 2.575 |
| 4 | 0.729 | 0 | 2.282 |
| 5 | 0.577 | 0 | 2.115 |
| 6 | 0.483 | 0 | 2.004 |
Individual/Moving Range (I-MR) Chart
When to Use
- Long cycle time
- Destructive testing
- Expensive testing
- Batch processes
Control Limit Formulas
I Chart:
UCL = X̄ + 2.66 × MR̄
CL = X̄
LCL = X̄ - 2.66 × MR̄
MR Chart:
UCL = 3.267 × MR̄
CL = MR̄
LCL = 0
Out-of-Control Rules
Western Electric Rules (Standard)
| Rule | Pattern | Indicates |
|---|---|---|
| Rule 1 | 1 point beyond 3σ | Sudden shift |
| Rule 2 | 8 points in a row on same side of CL (some sources: 9) | Process shift/mean shift |
| Rule 3 | 6 points in a row trending (up or down) | Trend/drift |
| Rule 4 | 14 points in a row alternating up/down | Over-adjustment |
Nelson Rules (Extended)
| Rule | Pattern |
|---|---|
| Rule 5 | 2 of 3 points beyond 2σ (same side) |
| Rule 6 | 4 of 5 points beyond 1σ (same side) |
| Rule 7 | 15 points in a row within 1σ of CL |
| Rule 8 | 8 points beyond 1σ (both sides) |
MNMUK Standard
Use Rules 1-4 (Western Electric) as standard. Apply Nelson rules for critical characteristics or detailed analysis.
Important: Western Electric Rule 2 triggers at 7 or more consecutive points on one side of the centerline (some references cite 8 or 9 — the broadly accepted standard is that 7+ points on one side constitutes an out-of-control signal requiring investigation). A run of 7 consecutive points on one side of the centerline IS an out-of-control condition.
Process Capability
Indices Overview
| Index | Measures | Formula |
|---|---|---|
| Cp | Potential capability (spread) | (USL - LSL) / 6σ |
| Cpk | Actual capability (considers centering) | Min(Cpu, Cpl) |
| Pp | Process performance (spread) | (USL - LSL) / 6s |
| Ppk | Process performance (considers centering) | Min(Ppu, Ppl) |
Key Difference: Cp/Cpk vs Pp/Ppk
| Aspect | Cp/Cpk | Pp/Ppk |
|---|---|---|
| Variation estimate | Within-subgroup (R̄/d₂ or S̄/c₄) | Overall (sample std dev) |
| Represents | Process potential | Process performance |
| Use when | Process in control | Initial assessment |
| Typically | Higher | Lower |
Capability Formulas
Cp (Process Potential):
Cp = (USL - LSL) / 6σ
Where σ = R̄/d₂ (within-subgroup estimate)
Cpk (Process Capability):
Cpu = (USL - X̄̄) / 3σ
Cpl = (X̄̄ - LSL) / 3σ
Cpk = Min(Cpu, Cpl)
Pp (Process Performance):
Pp = (USL - LSL) / 6s
Where s = sample standard deviation
Ppk (Process Performance Index):
Ppu = (USL - X̄) / 3s
Ppl = (X̄ - LSL) / 3s
Ppk = Min(Ppu, Ppl)
d₂ Constants
| n | d₂ |
|---|---|
| 2 | 1.128 |
| 3 | 1.693 |
| 4 | 2.059 |
| 5 | 2.326 |
| 6 | 2.534 |
Capability Targets
Automotive Industry Standards
| Index | Minimum | Preferred | For CC |
|---|---|---|---|
| Cpk | 1.33 | 1.67 | 1.67 |
| Ppk | 1.33 | 1.67 | 1.67 |
Interpretation
| Cpk Value | PPM (one tail) | Interpretation |
|---|---|---|
| 0.67 | 22,750 | Poor, not capable |
| 1.00 | 1,350 | Barely capable |
| 1.33 | 32 | Capable (minimum automotive) |
| 1.50 | 3.4 | Good |
| 1.67 | 0.3 | Very good (CC target) |
| 2.00 | 0.001 | Excellent |
Capability Study Process
Step 1: Plan the Study
- Identify characteristic
- Select measurement system (verify MSA)
- Determine sample size (minimum 30, prefer 50-100)
- Define sampling method
Step 2: Collect Data
- Collect samples under normal conditions
- Record in time order
- Document any special events
Step 3: Analyze Data
- Create histogram (check distribution)
- Check normality
- Calculate statistics
- Create control chart
- Check for statistical control
Step 4: Calculate Capability
- If in control: Calculate Cp, Cpk
- If not in control: Address special causes first, or report Pp, Ppk only
- Compare to requirements
Step 5: Interpret and Act
- Is capability adequate?
- What actions needed?
- Document results
Pre-Control (Alternative to SPC)
When to Use Pre-Control
- Very capable processes (Cpk >1.33)
- Short runs
- Quick setup verification
- Simpler than SPC
Pre-Control Zones
┌─────────────────────────────────────────────┐
│ RED ZONE │ → Stop, adjust
├─────────────────────────────────────────────┤
│ YELLOW ZONE │ → Caution
├─────────────────────────────────────────────┤
│ GREEN ZONE (Middle 50%) │ → OK
├─────────────────────────────────────────────┤
│ YELLOW ZONE │ → Caution
├─────────────────────────────────────────────┤
│ RED ZONE │ → Stop, adjust
└─────────────────────────────────────────────┘
LSL Target USL
Pre-Control Rules
- Startup: 5 consecutive in Green = run production
- Running:
- Both in Green → Continue
- One Yellow → Check again immediately
- Both Yellow → Investigate/adjust
- Red → Stop, investigate
Output Format
When generating SPC content:
# SPC Analysis
## Characteristic Information
| Field | Value |
|-------|-------|
| **Characteristic** | [Description] |
| **Specification** | [LSL - USL] |
| **Target** | [Nominal] |
| **Chart Type** | [X-bar/R, I-MR, etc.] |
## Control Chart Data
| Subgroup | X̄ (or X) | R (or MR) |
|----------|----------|-----------|
| 1 | | |
| ... | | |
## Control Limits
| Chart | LCL | CL | UCL |
|-------|-----|----|----|
| X-bar | | | |
| R | | | |
## Process Capability
| Index | Value | Requirement | Status |
|-------|-------|-------------|--------|
| Cpk | | ≥1.33 | PASS/FAIL |
| Ppk | | ≥1.33 | PASS/FAIL |
## Assessment
- In Control: Yes / No
- Capable: Yes / No
- Actions Required: [List]
Examples
Example 1 — Selecting and setting up a control chart
User: "We're machining a bore diameter on a CNC lathe, subgroup of 5 parts every hour. What chart should we use and what are the control limits?"
Output: Recommends an X-bar/R chart per Control Chart Selection (subgroups n=2-9), calculates UCL/CL/LCL using the A₂/D₃/D₄ constants for n=5, and flags the minimum 20-25 subgroups needed before finalizing limits per the X-bar/R Chart Setup guidance.
Example 2 — Interpreting an out-of-control signal
User: "Our control chart shows 8 consecutive points above the centerline. Is this out of control, and what should we do?"
Output: Identifies this as a Rule 2 violation (run of 7+ points on one side of centerline) per Out-of-Control Rules, explains it indicates a process/mean shift (special cause variation), and recommends investigation per the MNMUK standard (Western Electric Rules 1-4).
Example 3 — Capability assessment for PPAP
User: "Customer wants Ppk for PPAP submission on a critical characteristic. We measured Cpk = 1.45 in production but haven't calculated Ppk yet."
Output: Distinguishes Cpk (within-subgroup, process potential) from Ppk (overall variation, process performance) per the Key Difference: Cp/Cpk vs Pp/Ppk table, calculates Ppk from the overall sample standard deviation, and compares to the CC target of ≥1.67 per Capability Targets, flagging if Ppk falls short of Cpk (indicating between-subgroup variation exists).
Integration with Related Skills
ControlPlan
Control Plan specifies SPC requirements:
- Which characteristics require SPC
- Sample size and frequency
- Reaction to out-of-control
Load: read ~/.claude/skills/Controlplan/SKILL.md
MSA
SPC validity requires adequate measurement system:
- ndc ≥5 for meaningful SPC
- Poor MSA = poor SPC decisions
- Verify MSA before starting SPC
Load: read ~/.claude/skills/Msa/SKILL.md
AutomotiveManufacturing
Work instructions should include SPC procedures:
- How to collect data
- How to plot points
- How to interpret charts
- What to do when out of control
Load: read ~/.claude/skills/Automotivemanufacturing/SKILL.md
Supplementary Resources
For detailed guidance:
read ~/.claude/skills/Spc/CLAUDE.md
For capability study template:
read ~/.claude/skills/Spc/templates/capability-study.md
For control chart selection:
read ~/.claude/skills/Spc/reference/control-chart-selection.md
For capability indices:
read ~/.claude/skills/Spc/reference/capability-indices.md
For out-of-control rules:
read ~/.claude/skills/Spc/reference/out-of-control-rules.md