| 摘要: | 焊接在現代製造業中扮演著至關重要的角色，是連接材料的關鍵工藝，廣泛應用於汽車、航空航太及重工業等領域。本研究在探討公司導入協作型焊接機器人（半自動化）並結合AI Training系統後，對焊道品質的影響、焊工對自動化技術的認知、學習態度及專注度。本研究將6名受測者分為實驗組及控制組，控制組直接使用協作型機器人的Cobots系統，實驗組加入AI Training系統作為輔助使用Cobots系統。進行簡單、中等、困難程度的焊接任務實驗，共計五週。爾後進行問卷和訪談調查，並結合實驗所得的資料進行分析如下。
首先，AI Training系統的導入對提升焊工的系統操作理解及焊道品質具有顯著影響。與未使用 AI Training 的控制組相比，實驗組受測者在系統操作理解與焊接品質上均表現更優異，特別是在後測中平均成績提升超過30%，顯示 AI Training能顯著提升焊接精準度與穩定性。AI Training系統更激發了焊工的學習動機與興趣，特別是透過視覺化焊道定位與友善的操作界面，讓受測者能更投入學習，且減少焊接錯誤率。起初部分受測者會對技術存有抗拒心理，但透過任務學習逐漸建立信心並展現更正向的學習態度。研究也發現，使用AI Training系統的焊工在學習專注度上顯著高於控制組，其在中等及困難任務中的專注力均有所提升，表明系統對專注力的正面影響並促進實際操作成效。最後從問卷與訪談中得知，多數焊工對協作型焊接機器人的Cobots系統及AI Training系統持高度認可態度。實驗組更認為AI Training系統不僅降低焊接參數設定的難度，還提升了工作效率與操作信心。
本研究也收集了焊工對於半自動化焊接設備的使用體驗及其對未來智慧焊接技術的看法。受測者普遍認為此技術能促進焊接效率與品質的提升，並對未來智慧化、自動化的發展抱有高度期待。本研究最後提出相關建議，以期推動製造業的焊接技術朝向智慧化、自動化發展，並提供有價值的參考。;Welding is a critical process in modern manufacturing, serving as a key method for joining materials. It is extensively employed across industries such as automotive, aerospace, and heavy machinery. This study investigates the impact of integrating collaborative welding robots (semi-automated) with an AI training system on welding quality, as well as workers’ perceptions of automation, learning attitudes, and levels of concentration. Six participants were divided into an experimental group and a control group. The control group used the collaborative robots (Cobots) system directly, while the experimental group utilized the Cobots system with AI Training assistance. The study involved welding tasks of varying complexity (simple, moderate, and advanced) conducted over five weeks. Surveys and interviews were subsequently carried out, and the experimental data were analyzed as follows:
The results demonstrate that the AI Training system significantly enhances workers′ understanding of system operations and weld quality. Compared to the control group, the experimental group showed superior performance, with post-test scores increasing by over 30% on average, indicating the effectiveness of AI Training in improving welding accuracy and stability. The AI Training system also stimulated workers’ motivation and interest in learning, especially through its visualized weld path positioning and user-friendly interface, encouraging greater engagement and reducing welding errors. Initially, some participants exhibited resistance to the technology, but through task-based learning, they gradually gained confidence and adopted a more positive attitude.
The study also revealed that workers using the AI Training system demonstrated significantly higher levels of focus than the control group, particularly during moderate and challenging tasks. This indicates that the system positively influences focus and enhances practical performance. Furthermore, surveys and interviews indicated that most workers held a highly favorable attitude toward the Cobots and AI Training systems. Participants in the experimental group reported that the AI Training system not only reduced the complexity of welding parameter settings but also improved efficiency and confidence in operations.
In addition, the study gathered insights into workers’ experiences with semi-automated systems, and their perspectives on the future of intelligent welding technologies. Participants generally acknowledged the potential of these technologies to improve welding efficiency and quality and expressed optimism regarding the advancement of intelligent and automated welding solutions. This study concludes by offering recommendations to guide the development of welding technology toward greater intelligence and automation, providing a valuable reference for both industry and academia. |
