Maturity models for IT, Agile, DevOps, TOGAF, Six Sigma, P3M3, etc.
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Updated
Aug 20, 2026
Maturity models for IT, Agile, DevOps, TOGAF, Six Sigma, P3M3, etc.
Python toolkit for analysis of industrial process data; multivariate analysis, designed experiments, process monitoring.
A Grafana panel plugin for monitoring process stability over time. Supports Xbar-R, Xbar-S, and XmR charts with automatic calculation of control limits.
Course repository for learning R or Python for Cornell course SYSEN 5300: Systems Engineering and Six Sigma for the Design and Operation of Reliable Systems
AI skill for Claude Code and Codex that helps agents write correct R for Six Sigma and SPC work, including control charts, capability analysis, hypothesis tests, and ANOVA, with a method-selection layer that recommends the right technique from a plain-English problem description.
I improved customer experience at the Indian Market located in Milpitas using Lean Six Sigma techniques. The primary focus of this project was to reduce customer checkout time, managing stockouts and excess of inventory and optimize the store layout. A DMAIC approach was followed for the process improvement. The checkout time was reduced to 18% …
cryptocurruency trading bot
Catalogue of Articles, Projects, Papers and Resources relating to PSE
Preliminary Study for Depth Segmentation, this paper will be proceeding in KISM2021-Fall
WSQ Certified Lean Six Sigma Green Belt (CLSSGB) Training (TGS-2025055775) — 4-day / 32-hour DMAIC course with 25 hands-on activities, Excel datasets, slide deck, Learner Guide and Lesson Plan.
Process Analytics & Six Sigma in Python — integrated workflows for capability analysis, root cause analysis, and statistical process control.
A comprehensive collection of mathematical tools and utilities designed to support Lean Six Sigma practitioners in their process improvement journey
Quality Control Charts in Python. Inspired by the R qcc package.
This repository is a supplementary source of Quality Management.
SPC, process capability and Gage R&R for manufacturing: X-bar/R, X-bar/S and I-MR charts with Western Electric and Nelson rules, Cp/Cpk vs Pp/Ppk kept distinct, crossed Gage R&R (ANOVA and AIAG Average & Range). Verified against published results.
Project to predict price pass-through, contributing to the company's Revenue area, to predict the ideal SKU value based on various market and competitive variables.
This project, integrated with DevOps and JIRA, is capable of demonstrating and ensuring visibility of sprint deliverables and task status, completion percentage, and effort in real time per project.
Histogram panel with SPC control limits, bell curves, and capability indices.
Maturity Models
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