利用協作型焊接機器人及AI系統輔助學習焊接之研究

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曾珮涵(Pei-Han Tseng) 查詢紙本館藏

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網路學習科技研究所

論文名稱

利用協作型焊接機器人及AI系統輔助學習焊接之研究
(A Study of Using Collaborative Welding Robots and AI Systems for Facilitating Welding Learning)

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摘要(中)

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。

摘要(英)

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.

關鍵字(中)

★ 協作型焊接機器人
★ AI Training系統
★ 半自動化技術
★ 智慧焊接技術

關鍵字(英)

★ Collaborative Welding Robots
★ AI Training System
★ Semi-automation System
★ Intelligent Welding Technology

論文目次

摘要 I
Abstract II
致謝詞 IV
目錄 V
圖目錄 VIII
表目錄 X
第一章緒論 1
1.1 研究背景與動機 1
1.2 研究目的 2
1.3 研究問題 3
第二章文獻探討 4
2.1 焊接技術的學習與應用 4
2.1.1 焊接技術的基礎與學習特性 4
2.1.2 協作型焊接機器人的引入對學習的影響及應用 5
2.2 科技輔助工作 6
2.2.1 科技輔助工作的發展歷程 6
2.2.2 人工智慧在工作中的應用 7
2.3 協作型機器人的介紹 7
2.3.1 協作型機器人的歷史 7
2.3.2 協作型機器人的優勢 8
2.3.3 協作型機器人的相關研究 9
2.4 焊接技術與人機協作的挑戰與未來趨勢 11
2.4.1 焊接技術在智慧製造中的挑戰 11
2.4.2 未來焊接技術與協作機器人的發展趨勢 11
第三章研究系統 13
3.1 Cobots 系統 13
3.2 AI Training 系統 18
3.2.1 AI Training系統與Cobots系統間的關係 18
3.2.2 AI Training系統操作介紹 19
第四章研究方法 29
4.1 研究架構 29
4.1.1 控制變項 29
4.1.2 自變項 30
4.1.3 依變項 30
4.2 實驗流程 31
4.3 研究對象 33
4.4 實驗活動 34
4.4.1 簡單直線任務 34
4.4.2 中等多段式任務 36
4.4.3 困難3D任務 37
4.5 研究工具 39
4.6 資料蒐集與處理 39
第五章結果分析與討論 41
5.1 Cobots系統學習成就分析 41
5.1.1 前測及後測評比說明 41
5.1.2 前測及後測結果分析 42
5.2 受測者於實驗時之學習行為分析 48
5.3 AI Training介入後受測者的學習情形及影響 50
5.4 科技接受模型（TAM）問卷分析 52
5.4.1 系統易用性 52
5.4.2 系統有用性 54
5.4.3 活動有用性 55
5.4.4 滿意度 57
5.4.5 系統使用意圖 58
5.5 受測者對協作型焊接機器人的看法 59
第六章結論與建議 61
6.1 結論 61
6.2 限制與未來研究 62
參考文獻 64
附錄 69

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指導教授

黃武元(Wu-Yuin Hwang)

審核日期

2025-1-20

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