Statistical Process Control Charts Library for Humans

A toolkit for statistical process control using SQL

Python module for creating Shewhart statistical process control charts

Anomaly Detection: Nelson Rules for Control Chart - Python implementation

Statistical Process Monitoring in Julia

control chart pattern recognition with tensorflow, experiment conducted for Summer 2017 NSF REU at New Mexico State University

Fast Online Changepoint Detection via Functional Pruning CUSUM statistics

Social Networks Monitoring

This project is my thesis about computing a more accurate process capability index under dynamic process with mean shift and variance change.

Univariate Fast Initial Response Statistical Process Control with Taut Strings

Shewhart Control Chart and CUSUM (CUmulative SUM) Control Chart

Detecting Selected Non-Random Patterns with Individuals Control Charts

This repository contains the implementation of a multivariate control chart with dimension reduction techniques, namely Factor Analysis of Mixed Data (FAMD) and Autoencoder. The control chart is designed for detecting network intrusions using network data traffic.

Application designed for visualizing and monitoring control chart data in real-time. It leverages PyQt5 for an interactive and user-friendly interface, allowing users to dynamically explore data trends, and MySQL connector to retrieve data from database.