全球在工業4.0的影響下，各國紛紛提出因應的政策與目標，台灣則以生產力4.0為開端，後續發展出五大產業創新研發計畫等政策，許多產業面臨轉型的問題，工廠內部因智慧化的影響，原本以人力製造為主的工作逐漸被人工智慧所取代，人類開始擔憂自己的生存地位，然而得到實驗證實，全部以人類為主或以機器人為主的製造方式並非最佳的情況，而是透過人類與人工智慧進行合作的生產模式可以提升企業的績效。
因此本研究根據文獻探討和現況的資料，在一個人類與機器人的合作系統，又稱為人機協作系統，此系統由人和機器人組成的生產線，並且設定工作者的作業學習速度排序由最慢到最快，主要的目的為探討將生產線的人類工作者替換成機器人後的作業速度與原始生產線的差異，並且計算生產線的人類工作者替換成機器人後的作業成本差異來探討其對公司的效益。

Because of the influence of industry 4.0 all over the world, countries have proposed their policies and targets. In Taiwan, the government proposed Taiwan Productivity 4.0 Initiative first, then developed five major industrial innovation research and other policies. Many industries face the problem of transformation. The factories are affected by intelligence, so the works originally done by manpower are gradually replaced by artificial intelligence. And human starts to worry about their survival status. However, the experiments have confirmed that all human-based or all robot-based manufacturing methods are not the best way, cooperation between humans and artificial intelligence can improve the performance of the companies.
Therefore, based on literature review, we suggest a cooperative system between humans and robots. It is often called human-robot collaboration. Its progress velocity sorted by the slowest one to the fastest one, the main purpose is to explore the difference of velocity between the original production line and the human workers were substituted for the robots’ production lines. Moreover, we will calculate the cost for all the production line to see how the cost changes.

中文摘要 I
Abstract II
目錄 III
圖目錄 V
表目錄 VI
第一章 緒論 8
1-1研究背景與動機 8
1-2研究目的 13
1-3研究範疇 14
1-4研究流程架構及內容 14
第二章 文獻探討 15
2-1智慧工廠(Smart factory) 15
2-2人類和機器人間的互動 19
2-3生產線自我平衡和自我組織物流系統 23
2-4學習曲線 (Progress curve) 25
第三章 研究方法 26
3-1研究架構 26
3-2人機協作(Human-robot collaboration) 27
3-3模型基本假設及符號定義 27
3-4人類和機器人合作生產線模型建構 30
3-4-1學習曲線模型 31
3-4-2工作者作業比例函數 31
3-4-3工作者移動位置模型 31
3-4-4生產線的總成本函數 32
第四章 數值分析 34
4-1參數設定及數值分析 34
第五章 結論與未來研究方向 50
5-1結論 50
5-2研究限制與未來展望 50
參考文獻 52
英文參考文獻 52
中文參考文獻 53
附錄 54

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