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Methodology->
In this study, we have implemented SVM, MLP, and Decision Tree models for welding data classification.
Dataset
The experimental dataset provided by the Hanthec Organization in Korea consists of 15,000 observations related to welding processes.
The dataset includes five key parameters: a welding section length of 2.5 meters, a welding rod specification of 1.6 mm, welding speeds ranging from 200 to 500 mm/min, electrical currents between 200 and 380 amperes, and voltage levels from 29 to 48 volts.
The data reveals distinct operational clusters in welding speeds, specifically at 200-250 mm/min, 330-350 mm/min, and 450-500 mm/min.
These clusters are significant as they indicate optimal settings for achieving quality welds. The dataset not only facilitates the optimization of welding operations but also supports the development of predictive models for quality control.
By analyzing this data, manufacturers can enhance efficiency, reduce defects, and ensure consistent quality in welding processes. |
IEEE/ICACT20250115 Slide.07
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