Control Chart Analyzer
by a5c-ai
Statistical process control chart creation and analysis skill with control limit calculation and special cause detection
Skill Details
Repository Files
1 file in this skill directory
name: control-chart-analyzer 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
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
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
- One point beyond 3 sigma
- Two of three consecutive points beyond 2 sigma (same side)
- Four of five consecutive points beyond 1 sigma (same side)
- Eight consecutive points on one side of center line
Nelson Rules
- One point beyond Zone A (3 sigma)
- Nine points in a row on same side of center line
- Six points in a row, all increasing or decreasing
- Fourteen points in a row, alternating up and down
- Two of three points in Zone A or beyond (same side)
- Four of five points in Zone B or beyond (same side)
- Fifteen points in a row in Zone C
- 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
Related Skills
Team Composition Analysis
This skill should be used when the user asks to "plan team structure", "determine hiring needs", "design org chart", "calculate compensation", "plan equity allocation", or requests organizational design and headcount planning for a startup.
Startup Financial Modeling
This skill should be used when the user asks to "create financial projections", "build a financial model", "forecast revenue", "calculate burn rate", "estimate runway", "model cash flow", or requests 3-5 year financial planning for a startup.
Startup Metrics Framework
This skill should be used when the user asks about "key startup metrics", "SaaS metrics", "CAC and LTV", "unit economics", "burn multiple", "rule of 40", "marketplace metrics", or requests guidance on tracking and optimizing business performance metrics.
Market Sizing Analysis
This skill should be used when the user asks to "calculate TAM", "determine SAM", "estimate SOM", "size the market", "calculate market opportunity", "what's the total addressable market", or requests market sizing analysis for a startup or business opportunity.
Anndata
This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling large-scale biological datasets. Use when tasks involve AnnData objects, h5ad files, single-cell RNA-seq data, or integration with scanpy/scverse tools.
Geopandas
Python library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files. Use when working with geographic data for spatial analysis, geometric operations, coordinate transformations, spatial joins, overlay operations, choropleth mapping, or any task involving reading/writing/analyzing vector geographic data. Supports PostGIS databases, interactive maps, and integration with matplotlib/folium/cartopy. Use for tasks like buffer analysis, spatial joins between dat
Market Research Reports
Generate comprehensive market research reports (50+ pages) in the style of top consulting firms (McKinsey, BCG, Gartner). Features professional LaTeX formatting, extensive visual generation with scientific-schematics and generate-image, deep integration with research-lookup for data gathering, and multi-framework strategic analysis including Porter's Five Forces, PESTLE, SWOT, TAM/SAM/SOM, and BCG Matrix.
Plotly
Interactive scientific and statistical data visualization library for Python. Use when creating charts, plots, or visualizations including scatter plots, line charts, bar charts, heatmaps, 3D plots, geographic maps, statistical distributions, financial charts, and dashboards. Supports both quick visualizations (Plotly Express) and fine-grained customization (graph objects). Outputs interactive HTML or static images (PNG, PDF, SVG).
Excel Analysis
Analyze Excel spreadsheets, create pivot tables, generate charts, and perform data analysis. Use when analyzing Excel files, spreadsheets, tabular data, or .xlsx files.
Neurokit2
Comprehensive biosignal processing toolkit for analyzing physiological data including ECG, EEG, EDA, RSP, PPG, EMG, and EOG signals. Use this skill when processing cardiovascular signals, brain activity, electrodermal responses, respiratory patterns, muscle activity, or eye movements. Applicable for heart rate variability analysis, event-related potentials, complexity measures, autonomic nervous system assessment, psychophysiology research, and multi-modal physiological signal integration.
