隨著科技與工業的進步與開發,機器的機械化與自動化已逐漸減少人力的付出,但在目前的營建環境裡仍有許多作業須仰賴人力的進行,且無合適之自動化機具可供協助作業。在營建業上,工人的生產力影響工程的進度與成本,不論工程的施工規劃、估價、排程、施工過程的時間與成本都與工人的生產力有相當的關係,而對於生產力的評估調查方法有:問卷調查法、面談法、工地效率評估法、抽樣調查法、短時效率評估法等等,其調查方式須以現場觀測與人工記錄之方式進行,且大多只能觀察局部作業而未能觀察到整體的作業。因此,本研究為了減少人力之成本並提高生產力調查結果之可靠度,擬探討利用耗氧量與心搏率自動量測方式進行生產力調查之可行性。 本研究採試驗室實驗方式,徵集12位受測者參與實驗,利用系統模板作業,模擬工地現況並同時量測受測者作業之耗氧量與心搏率,藉由所得之平均耗氧量與平均心搏率進行變異數分析。研究結果顯示,單一作業項目檢定結果得知大部分之作業項目都能利用工作耗氧量與心搏率進行區別,僅極少部分作業無法進行區分。而將作業項目分類為直接工作、間接工作及無工作三類後再進行群組分類檢定,其檢定結果為類別間具有顯著差異,證明利用工作耗氧量與心搏率可明顯有效區別系統模板工作之直接工作、間接工作及無工作狀態,應可有效使用於生產力之評估。
As the advancement and development of technology and industry continue, mechanism and automation of machines have helped reducing manpower. Nonetheless, many operations in the construction industry still require manpower since there aren’t appropriate automatic machines and tools to assist. In the construction industry, workers’ productivity closely influences the progress and cost of construction works. Execution planning, pricing, scheduling, execution duration and construction costs are all significantly related to the productivity of workers. The assessment methods and surveys over productivity commonly applied include: questionnaire survey, interview, on-site efficiency assessment, sampling survey, short duration efficiency assessment, etc. The surveys involve on-site observations and measurements as well as manual recording. In addition, most observations could only be made on partial operations instead of entire operations. Therefore, for reducing manpower cost and improving reliability of the results of productivity survey, this study attempts to discuss the feasibility of conducting productivity survey by way of automatic measurements of oxygen consumption and heart rate. In this study, the experiments were conducted in a laboratory. 12 objects were invited to join in the experiments. The practical operation of system framework at construction sites was simulated. Meanwhile, oxygen consumption and heart rate of the objects were measured. The average oxygen consumption and average heart rate obtained were used for making analysis of variance. Based on the test result against each type of work, it was suggested that most types of works could be categorized by oxygen consumption and heart rate while few types of works could not. Consequently, system framework was categorized into direct work, indirect work and no work followed by group testing. The test results showed that significant differences existed among those categories. Finally, it was proved that oxygen consumption and heart rate could effectively help to identify direct work, indirect work and no work under system framework and assess related productivity accordingly.
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