A set of symbols, footprints and 3d models of the basic components from JLCPCB's smt assembly
A free open source cross-platform C++ library for parsing ODB++ Design archives, accessing their data, and building net list product models. Exposed via a REST API packaged inside of a Docker image.
ESP32 Bus Interface for ABB-Welcome and Busch-Welcome
Auto place components into pcbnew from a centroid file. Useful for maintaining a common board form factor.
GPU-Accelerated Web Based EDA Manufacturing Artwork Viewer
A PCB viewer web component for IPC-2581 format with support of Angular framework.
Find parts from JLCPCB matching design constraints (resistance values, capacitance, tolerance etc.)
Raspberry pi hat for the elegoo mars 4 dlp UV projector. Implements SPI data transfer for the DLPC1438.
This guide will teach you all the basics of KiCad from schematic building to PCB design. It will also teach you how to add libraries, create your own symbols & footprints, export the drill and gerber files, and many more tips to get you started on your KiCad journey!
Raspberry pi hat for the Anycubic Photon Ultra UV projector. Implements parallel video for the DLPC1438.
STM32L0 and ESP32 MCU based PCB for PID and IOT applications designed using KiCad.
This repository includes a collection of electronic PCB designs and custom KiCad libraries. It features various hardware projects, reusable components, and detailed documentation for learning and development.
convert SVG to STL for 3D printing (PCB making)
A CLI Tool to automate the generation of ALL the required drilling, cutting and trace engraving Gcode files, given ONLY the Gerber files. Also supports the Simulation of tool paths.
Bring own applications to shopfloor - PCB quality re-check and production optimization based on AI techonology
The PCB roller transfer machine (or laminator machine) is a machine designed to thermally transfer toner printed on paper to a blank Printed Circuit Board.
This project is designed to detect and describe defects in printed circuit boards (PCBs) using a YOLOv5 deep learning model. It identifies common defects like missing holes, open circuits, and short circuits, and provides bounding boxes with confidence levels for each detection.
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