Plugin for abaqus to generate user subroutines in welding and Additive Manufacturing modeling

Thermal-Fluid Dynamics Solver for Advanced Manufacturing Applications

Component data sheets, busbars and files needed to build no-weld BMS DKblock style battery packs. Here is a YouTube video, courtesy of Nick Jobbitt of a 10 block build, sped up: https://www.youtube.com/watch?v=V05_WOhEqQg&feature=youtu.be ................ DKblock2 parts available on ebay search "DKblock

The welding data exchange format

A simple script for welding in ANSYS APDL with Goldak heat source

CNN for predicting the quality of the welding

Motoman MA1400 simulation for Gazebo and ROS

Detection of welding defects with AI (YOLO11)

Codes that model the temperature profile during welding (Analytical and Semi-Analytical)

MIG welder wire feeder using step motor. Provides precision control of speed. In-place replacement for DC motor. Also adds 2-1 mode for welding thin sheet metal.

System control and programming for Industrial Robots(for Hwashi)

Project based on programming mechatronics Robots on Robot Studio(ABB) under guidance of APS-GmbH European Center, Germany.

Welding 101 is a VR training simulation that offers a safe, cost-effective way to learn welding techniques with real-time AI feedback. It integrates metallurgy education and covers all major welding methods. The project aims to enhance hands-on learning and plans to implement teleoperation for remote welding control through virtual reality.

🛠️ Useful utilities related to welding

A circular motion welding planner for various pipe diameters using Aubo I3 robot arm with ROS Noetic & Moveit

Repository providing code and datasets used for the online 2021 IIW Intermediate Meeting C-XII meeting 30.-31.03.2021 .

Prototype computer vision software for a system for welding steel tubes into frames.

[SolidWorks] Weldment chassis of airport support vehicle for carry trailers with suitcases, TLD JET-16 🚚💼✈️

An app containing a set of useful welding tools 🛠️

This project focuses on predicting welding quality based on time series data of electrical current and voltage measurements. The analysis employs various machine learning techniques to extract meaningful features from welding process data, identify patterns through clustering, and build predictive models for quality classification.