---
name: control-chart-analyzer-af6f2ff67ad7
description: Statistical process control chart creation and analysis skill with control limit calculation and special cause detection
allowed-tools:
  - Read
  - Write
  - Glob
  - Grep
  - Edit
metadata:
  specialization: operations
  domain: business
  category: six-sigma-spc
graph:
  domains: [domain:operations]
  skillAreas: [skill-area:statistical-analysis, skill-area:data-analytics, skill-area:business-analysis]
  workflows: [workflow:vendor-onboarding, workflow:vendor-evaluation]
  roles: [role:operations-analyst, role:data-analyst, role:business-analyst]
---

# Control Chart Analyzer

## Overview

The Control Chart Analyzer skill provides comprehensive capabilities for creating and analyzing statistical process control charts. It supports multiple chart types, control limit calculation, and automated detection of special cause variation using industry-standard rules.

## Capabilities

- X-bar and R chart creation
- Individual and Moving Range (I-MR) charts
- p-chart and np-chart generation
- c-chart and u-chart analysis
- Control limit calculation
- Nelson rules application
- Western Electric rules detection
- Out-of-control signal alerting

## Used By Processes

- SIX-002: Statistical Process Control Implementation
- SIX-003: Process Capability Analysis
- QMS-003: Quality Audit Management

## Tools and Libraries

- Minitab API
- JMP
- Python scipy/statsmodels
- R quality packages

## Usage

```yaml
skill: control-chart-analyzer
inputs:
  data_type: "continuous"  # continuous | attribute
  chart_type: "xbar_r"  # xbar_r | xbar_s | imr | p | np | c | u
  subgroup_size: 5
  data:
    - subgroup: [10.2, 10.1, 10.3, 10.0, 10.2]
    - subgroup: [10.4, 10.3, 10.2, 10.5, 10.3]
  specification_limits:
    usl: 10.8
    lsl: 9.2
    target: 10.0
outputs:
  - control_chart
  - control_limits
  - out_of_control_signals
  - rule_violations
  - recommendations
```

## Chart Selection Guide

| Data Type | Subgroup Size | Recommended Chart |
|-----------|---------------|-------------------|
| Continuous | 1 | I-MR |
| Continuous | 2-10 | X-bar & R |
| Continuous | >10 | X-bar & S |
| Attribute (defectives) | Variable | p-chart |
| Attribute (defectives) | Constant | np-chart |
| Attribute (defects) | Variable area | u-chart |
| Attribute (defects) | Constant area | c-chart |

## Western Electric Rules

1. One point beyond 3 sigma
2. Two of three consecutive points beyond 2 sigma (same side)
3. Four of five consecutive points beyond 1 sigma (same side)
4. Eight consecutive points on one side of center line

## Nelson Rules

1. One point beyond Zone A (3 sigma)
2. Nine points in a row on same side of center line
3. Six points in a row, all increasing or decreasing
4. Fourteen points in a row, alternating up and down
5. Two of three points in Zone A or beyond (same side)
6. Four of five points in Zone B or beyond (same side)
7. Fifteen points in a row in Zone C
8. Eight points in a row on both sides with none in Zone C

## Integration Points

- Manufacturing Execution Systems
- Quality Management Systems
- Real-time data platforms
- Alerting systems


---
Source attribution: a5c-ai
Original project: https://github.com/a5c-ai/babysitter
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 Gabriel Moreira

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: a5c-ai
Original project: https://github.com/a5c-ai/babysitter
Attribution basis: Upstream repository explicitly recorded in package mirror path

Fields of work: Data & Analytics, Operations, Project & Program Management
Roles: Business Process Analyst, Data Analyst, Operations Manager, Project Manager
Specialties: API
Tools: Jmp, R Quality Packages, Python Scipy/Statsmodels, Minitab Api
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 39ec3436461224caaa0c4bc2d21aa57baa371333a9f69c21a582a1140549ec41