Simulated Dataset for Edge-Based Defect Prediction in Robotic Welding

Description

This dataset is a simulated collection of 300 samples representing real-time robotic welding process parameters. It includes arc voltage, welding current, welding speed, wire feed speed, gas flow rate, torch angle, and base metal temperature. Each entry is labeled with a binary defect tag (0 = no defect, 1 = defect) based on parameter thresholds that reflect known causes of welding quality issues. The dataset was generated using Python for research in edge computing applications, machine learning model development, and defect prediction in smart manufacturing environments. Note: This is a synthetic dataset created for academic use only.

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