A Grafana panel plugin for monitoring process stability over time. Supports Xbar-R, Xbar-S, and XmR charts with automatic calculation of control limits.
AI-powered Statistical Process Control, MSA, and Process Capability analysis. Upload data, ask in plain English, get charts and reports.
Analyzing Electric Circuit Board Defect Dataset for Statistical Process Control using various Quality Tools & Techniques for the enhancement of Quality Control in a Manufacturing Setting.
25 hands-on WSQ Certified Lean Six Sigma Green Belt labs across the full DMAIC roadmap — project charter, VOC/CTQ, Kano, SIPOC, value stream mapping, sampling and sample size, MSA/Gage R&R, DPMO and process capability (Cp/Cpk), Pareto and run charts, hypothesis testing, correlation and regression, FMEA, DOE and SPC control plans. 4-day course.
Perform Six Sigma Data Analysis using Python
Simple Cp Cpk calculator with Python example and web tool
Browser-based Statistical Process Control (SPC) tool with 7 chart types, process capability analysis, and distribution visualization. Vanilla HTML/CSS/JS.
JMP-based lithography line-width CD control, SPC, ANOVA, and process capability analysis using NIST wafer data.
8 hands-on Certified Lean Six Sigma Black Belt labs covering DMAIC, project charter, VOC, SIPOC, MSA, capability, hypothesis testing, regression, DOE, FMEA, SPC, control plans, benefits realization, and exam review.
반도체 공정변경(POR vs NEW) 평가 Claude Code 플러그인 — 측정 엑셀 2개로 Ppk·t-test·판정·Evaluation Result 슬라이드 HTML 생성 (Minitab 불필요)
Process capability analysis of manufacturing dataset in Excel
Open-source Power BI custom visual for statistical distributions: manual bin control, normal curve, LSL/USL + Cp/Cpk, sigma level + DPMO, Anderson-Darling p-value, Q-Q plot, box plot. 6 languages. MIT.
Simulated cover glass manufacturing quality analytics project for MQE portfolio
Virtual 9-stage TSMC 28nm fab simulation in JMP using sequential RSM and Six Sigma (DMAIC). Achieved >90% yield, tracked cascading defects, and optimized Cpk from 0.94 to 3.84.
Gatekeeper is a personal/internal calculation aid, not a validated quality system. Treat every number it produces as a calculation to be reviewed by a qualified person, not as a substitute for a validated SPC software package (Q-DAS, Minitab, etc.) when a real production release or DTS decision is on the line.
Statistical process control and process capability analysis of a pretzel manufacturing system using control charts, hypothesis testing, and Six Sigma methods.
Python-based SPC and process capability analysis for simulated manufacturing quality data.
Automated Process Capability Analysis (SPC) tool for massive production datasets. Supports Normal and Non-Normal distributions, Box-Cox/Johnson transformations, and automated subgroup reporting. Built as a high-performance alternative to manual statistical software.
Real-time manufacturing quality prioritization system combining SPC, predictive analytics and Power BI for industrial decision support.
Python toolkit for Cp/Cpk, PFMEA, OEE, Gauge R&R, SPC, process data, and manufacturing improvement.
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