AI-powered Statistical Process Control, MSA, and Process Capability analysis. Upload data, ask in plain English, get charts and reports.
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.
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.
Process behavior charts (control charts / SPC) for Python — XmR, Xbar-S, histograms, capability, Taguchi loss. Implements Bishop's Variance Analysis System with chart math validated against published reference results.
WSQ Certified Lean Six Sigma Black Belt (CLSSBB) Training, TGS-2024051900. 5-day practitioner course with 34 hands-on activity packs and a capstone improvement project, plus the full slide deck, Learner Guide and Lesson Plan.
COMSOL 6.4 model of an APCVD poly-Si reactor on a 300 mm wafer | inlet redesign cuts non-uniformity 180% to 3.3% | 14-run CCD, Gaussian-process surrogate, Monte Carlo Cpk, 3D asymmetric exhaust
WSQ courseware for Statistical Process Control (SPC) in Manufacturing (TGS-2026064862): 86-slide deck, Lesson Plan, Learner Guide, 12 hands-on activities and Excel worksheets covering control charts, Cp/Cpk capability and out-of-control root cause analysis. 1-day course by Tertiary Infotech Academy.
Supplier quality engineering control tower: SPC, process capability, Pareto and root-cause analysis applied end to end on a synthetic manufacturing dataset. Portfolio project.
Reproducible industrial quality-inspection system using OpenCV for defect detection, dimensional measurement, false accept/reject analysis, SPC, and Cp/Cpk evaluation.
製造業における品質管理のための工程能力解析ツール
Simulated cover glass manufacturing quality analytics project for MQE portfolio
Physics-based cosmetic finish process-capability simulator for anodizing and PVD thin-film coatings
Desktop app for optical and display measurement data analysis: process capability (Ppk/Cpk), AICc best-fit distribution, box plots, correlation, and JMP script generation.
Talaşlı imalat ve CNC işleme merkezleri için hepsi-bir-arada mühendislik istasyonu: SPC (Cp, Cpk), ISO 286 Tolerans & Geçme, G-Kod Simülatörü & Strok Denetimi, Kesme Gücü, Yüzey Pürüzlülüğü (Ra), Parça Maliyeti ve Kurumsal PDF Raporlama.
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.
Automated characterization test rig demonstrating design-of-experiments: sweeps a device under test across its envelope, models the instrument, computes Cpk/yield, and shows a failure corner that one-factor-at-a-time testing misses but full-factorial DOE catches. Live shmoo explorer included.
Thermal oxidation of silicon in Python: Deal–Grove kinetics with Massoud thin-oxide corrections, furnace recipe integration, Monte Carlo process capability, and oxidation-enhanced diffusion.
Python-based SPC and process capability analysis for simulated manufacturing quality data.
Tolerance stack-up and process capability analysis with worst-case, RSS and Monte Carlo simulation.
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