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研究生:蕭文達
研究生(外文):Wen-Ta Hsiao
論文名稱:考慮勞工能量消耗與總工時之最佳化派工模式
論文名稱(外文):A Labor Work Assignment Model Considering Energy Expenditure and Work Duration
指導教授:謝孟勳謝孟勳引用關係
指導教授(外文):Machine Hsie
學位類別:博士
校院名稱:國立中興大學
系所名稱:土木工程學系所
學門:工程學門
學類:土木工程學類
論文種類:學術論文
論文出版年:2009
畢業學年度:97
語文別:中文
論文頁數:183
中文關鍵詞:生理作業能力最大可接受工作時間能量消耗最大攝氧量人因工程基因演算法多目標最佳化
外文關鍵詞:physical working capacitymaximum acceptable work durationphysical energy expendituremaximum oxygen uptakeergonomicsgenetic algorithmmultiobjective optimization
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營建業之工作中有許多是屬於重體力之作業,且仍有相當多之作業必須仰仗人力,尚無合適之自動化機具可供協助,是故營建勞工常會有較大之體力付出,或是需使用較不符合人體工學之姿式進行工作。當勞工之體力負荷超出個人可接受工作負荷時,若未能給予適當休息,就容易因精神或肌肉骨骼過度疲勞,進而影響勞工之生產力及工作品質,更可能造成營建勞工身體累積性傷害或意外事故發生。傳統之排程將勞工視為是一種單純的資源,認為每位勞工的身體狀況與工作能力都是相同的,未將工作內容可能對勞工肌肉骨骼造成影響的問題考慮於工作排程中,是故營建勞工因不合適之工作安排,而造成肌肉骨骼傷害之案件層出不窮。依據行政院勞工委員會對台灣地區營建業之勞工進行抽樣調查,結果發現531位受測者中約有70%認為自己因從事的工作,造成肌肉骨骼的痠痛或傷害。在營建工程的排程過程中,實應將工作負荷對勞工身體健康之影響納入考量,是故在工作排程或派工過程中加入合適的派工機制或手法實有其必要性。
本研究考量了勞工的生理因素,利用人因工程(Ergonomics)的理論,並結合多目標基因演算法,及柏拉圖最佳解(Pareto Optimal Solution)的觀念,建置了一套雙目標之工作/休息最佳派工理論模型。建立之模型可同時考量工程總工作時間最小化,及勞工因工作時間超出其最大允許工作時間(Maximum Acceptable Work Duration, MAWD)造成之超額能量支出最小化的兩個目標。
經假設案例驗證,本研究建置之模型,確實可以有效的依照設定之條件,進行最佳之工作安排及勞工指派,以避免不必要之時間花費及勞工能量消耗,並提供多個可行派工模式供管理者權衡選用,且可列出所選用之派工模式的整體派工表及個人派工表,以為派工及工作執行之依據。
Construction workers usually perform jobs that involve overexertions and awkward postures in restricted working environments with less use of machinery. Their work, as a result, is physically very demanding. Physically demanding work may not only lead to physical fatigue but also lead to negative problems such as the loss of productivity, poor quality work, reduced job satisfaction, and possible musculoskeletal disorders. Possible preventive measures such as proper organization of work can be used to avoid physical fatigue in workers. The proper design of a work-rest schedule may be effective in improving a worker’s comfort, health, and productivity.
This research develops a theoretical model that can be used to create work-rest schedules for construction workers. Two objectives are proposed in the optimization processes when such schedules are created. These objectives include minimizing the time for completing jobs and minimizing any extra energy expended by laborers due to inappropriate work assignments that force them to work longer than the maximum acceptable work duration. A GA-based mechanism was developed to search the Pareto front, which is one of the effective ways for solving multiobjective optimization problems. Such a mechanism was implemented by computer programming using a numerical software tool called MATLAB. Theoretical examples demonstrated that the proposed model efficiently created work-rest schedules.
目錄
摘要 i
Abstract iii
誌謝 v
目錄 vii
表目錄 xi
圖目錄 xii
第一章 緒論 1
1.1、研究動機 1
1.2、研究目的 2
1.3、研究範圍 3
1.4、研究方法與流程 4
1.4.1、研究方法 4
1.4.2、研究流程 4
1.5、論文架構 6
第二章 文獻回顧 9
2.1、營建作業對勞工之傷害 9
2.2、專案排程 11
2.3、人因工程 15
2.4、多目標最佳化 23
2.5、小結 24
第三章 排程理論介紹 26
3.1、排程問題之分類 26
3.2、資源限制專案排程 29
3.3、派工法則 32
3.4、專案排程中之作業邏輯關係 34
3.5、小結 36
第四章 人因工程理論介紹 37
4.1、生理作業能力與最大耗氧量 38
4.2、可接受工作負荷 42
4.3、最大允許工作時間 43
4.4、需求休息時間 44
4.5、小結 46
第五章 模式求解工具-多目標基因演算法 47
5.1、概說 47
5.2、染色體編碼(Encoding) 49
5.3、適存值函數(Fitness Function) 52
5.4、選取機制(Selection) 54
5.5、交配機制(Crossover) 57
5.6、突變機制(Mutation) 63
5.7、終止條件 67
5.8、小結 68
第六章 考量能量消耗與工期之最佳化模型之建立 69
6.1、工作安排與資源分配 69
6.1.1、作業與勞工指派流程 70
6.1.2、派工法則之決定 73
6.2、基因演算模式 74
6.2.1、適存值計算 74
6.2.2、染色體編碼與結構 82
6.2.3、選取與複製 87
6.2.4、交配 87
6.2.5、突變 90
6.2.6、終止條件 91
6.3、小結 92
第七章 案例驗證與結果分析 93
7.1、演算參數敏感度分析 93
7.2、假設案例驗證 102
7.2.1、案例介紹 102
7.2.2、案例結果分析 106
7.3、小結 116
第八章 結論與建議 117
8.1、結論 117
8.2、未來研究方向與建議 119
參考文獻 121
中文部分 121
英文部分 125
附錄A 作業項目間無前後邏輯關係案例之整體派工表(Pareto Solution 1) 136
附錄B 作業項目間無前後邏輯關係案例之個別派工表 148
附錄C 作業項目間有前後邏輯關係案例之整體派工表(Pareto Solution 1) 160
附錄D 作業項目間有前後邏輯關係案例之個別派工表 172
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