wafer-map

STDF to Wafer Bin Map utility written in Python

Python utilities for loading, plotting, and editing wafer defect maps known as KLA Reference Files (KLARFs)

a kibana plugin to visualize the wafer map

This project aims to process 2D images of semiconductor silicon wafers to identify any defects on the wafers as well as their corresponding locations.

산학협력프로젝트: 머신러닝 기반 Wafer Map Defect Pattern Identification

Wafer map defect pattern classification with Multi-Input Neural Network using Convolutioal and Handcrafted Features

Interactive wafer map visualization and yield analysis for semiconductor test data. Rendering, spatial statistics, failure clustering, lot-level trends, and reticle analysis — pure ES modules, no dependencies.

Mask-aware wafer defect classification using a DenseNet-based CNN with explicit geometry masking and Grad-CAM explainability.

Desktop and browser wafer map viewer for semiconductor test data — Tauri v2, Rust/WASM parsers for STDF/ATDF/CSV/JSON/Parquet, wafermap rendering

半导体晶圆测试（CP）数据处理桌面工具：自动抓取 STDF → 内置解析器转 Excel → 离线交互式晶圆图 → 块状失效监测

Utility script for visualization of wafer properties from measurement data, intended for wafer evaluation in process development and production workflows.

Utility script for generating wafer-level measurement point layouts with configurable patterns and edge exclusion, designed for semiconductor process development and production workflows.

Automated semiconductor wafer defect pattern recognition on the WM-811K dataset using PyTorch. Implements custom CNN architectures, weighted loss handling for severe class imbalance, and end-to-end evaluation for yield analysis.

Utility script for visualization of wafer properties from measurement data, intended for wafer evaluation in process development and production workflows.

Wafer Map Defect Classification using Deep Convolutional Neural Networks (CNN) with TensorFlow/Keras on the WM-811K dataset.

Top Semiconductor Yield Management (Opensource) 🌟 Star if you like it! 🌟

웨이퍼 맵 불량 패턴 판독 에이전트 — 아는 패턴 분류 · 처음 보는 패턴 경고 · 코드가 검사하는 로컬 LLM 판독 카드 (WM-811K)

Automatic scratch detection in semiconductor wafer maps using engineered spatial features and XGBoost.

Leakage-aware WM-811K wafer-map classification with lot-level splitting, repeated-seed validation, cluster-bootstrap uncertainty, spatial diagnostics, and Grad-CAM.

EFA-aware wafer map failure pattern classification on WM-811K — calibrated confidence, selective prediction, honest evaluation