English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

As the pipes used in the shipbuilding industry are expensive of the materials themselves and require excellent welds performance, the latest high-performance welding methods and automation are urgently needed, the level of demand for pipe welding equipment products is increased, and the cost reduction for securing competitiveness in overseas markets is being developed. In pipe welding, the worker's proficiency has a great influence on the quality and productivity of the welds, and the demand for the welding process continues to increase as the number of skilled workers decreases. Recently, the welding industry has been involved in the Fourth Industrial Revolution, and several studies are being conducted to establish the smart factory and the high quality demand of products in the field of actual production and manufacturing. Deep learning, one of the artificial intelligence techniques, shows outstanding performance in recent areas such as object recognition, natural language processing and image classification through the development of computer computation processing speed. Therefore, in this study, 3D Scanner was used to obtain current voltage data through GTA welding using SA516-70 material and to identify the dimensions of bead width according to current voltage data. In addition, real-time current and voltage data and data obtained through 3D Scanner developed a DNN model to predict bead width.

A Study on the Prediction of Real-Time Bead Width Using a DNN Algorithm in GTA Welding