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Run deterministic statistical process control analyses like charts, capability, and tolerance intervals.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "shewhart-mcp" yet — see the docs or source repo.
Using this time-ordered measurement data, generate an appropriate control chart, calculate control limits, and flag possible out-of-control points and abnormal patterns: 12.1, 11.9, 12.0, 12.3, 12.2, 12.8, 12.4, 12.1, 11.8, 12.0.
Returns control chart results, upper and lower control limits, anomaly flags, and a brief process stability assessment.
Given a lower spec limit of 9.5 and an upper spec limit of 10.5, and the following sample data: 9.8, 10.1, 10.0, 9.9, 10.2, 10.3, 9.7, 10.1. Please calculate Cp and Cpk and determine whether the process is capable.
Outputs process capability indices, key statistics, and a short conclusion on whether requirements are met.
For the following sample data, calculate a two-sided tolerance interval that covers 95% of the population with 90% confidence, and explain what the interval means: 45.2, 44.9, 45.1, 45.4, 45.0, 44.8, 45.3, 45.1, 45.2, 44.9.
Provides the tolerance interval, notes on coverage and confidence, and a brief explanation of when to use it.
Monitor industrial process data and get anomaly analysis with actionable recommendations.
Monitor equipment health and query status, maintenance, and anomalies via MCP.
Run statistical analysis, probability calculations, and data processing through natural language.
Analyze overall equipment effectiveness, loss factors, and generate visual insights.
Enable AI agents to run project scheduling, CPM, PERT, and earned value analysis.
Perform math operations, solve equations, and support practical quantitative analysis tasks.