以往評估營建生產力之模式，由文獻發現有許多是應用多元線性迴歸法來分析，但是多元線性迴歸法對某些具有模(含)糊性質的生產力與影響因子，例如：生產力很低、低、普通、高或很高；天候很差、普通或很好等，需經由觀測人員或專家主觀的語意評估，此類模糊資訊或模糊變數的問題，卻無法有效處理。相反地，模糊迴歸分析已被認可克服此種類問題的有效方法。
本研究為尋求解決模糊資訊或模糊變數的問題，俾能提供更準確地估計工程作業之生產力，透過文獻回顧、專家訪談及研究推論後，再參考Pan et al.及本研究提出之模式以國道2號高速公路拓寬工程工程第H21A標為案例，建立以節塊懸臂工法施工作業及橋樑之墩柱基礎開挖、鋼筋綁紮及模板組立等生產力之模糊迴歸式。本研究模式的預估結果可建立作業生產力與其影響因子之關係式，協助進度管理者更合理、準確地估計作業生產力與需時；此外，由迴歸模式之係數正負號與數據大小，可瞭解變數對於作業工率之影響及其影響層面大小，進而回饋於改善與管控的重要影響變數。
有效而正確的生產力計算，除可提供規劃及設計單位對工期及成本之預估外，亦可做為業界於評估下包團隊工作效率之依據及參考。

In the past technical literature, modes of estimating construction work rate have been found analyzed by applying Multi Factor Line Regression Method. However, Multi Factor Line Regression Method can not effectively deal with productivity and impact factors with fuzzy properties. Fussy properties are such as very low, low or average unit rate and high or very high unit rate; poor, average, or good weather; expressions that need subjective semantic evaluations by observers, specialists, and problems with fuzzy information and fuzzy variables. On the contrary, Fuzzy Regression Analysis has been recognized to effectively overcome the problems just mentioned.
This study aims to seek for solutions for fuzzy information and fuzzy variables in order to provide more accurate estimation of construction operation unit rate. Through reviews of technical literature, interviews with experts and research inference, and reference to Pan et al. this study also brought up National Highway No.2 widening project tendering number H21A, H31, H61 as examples. In these constructions, the Fuzzy regression were established for the work rate of the cantilever construction with incremental launching method, foundation excavation of the bridge pier column, steel banding and template assembly. The expected results of this study may establish a correlation between the operation productivity and impact factors, so as to assist the schedule manager more sensibly, more accurately estimate operation unit rate and time demanded. Besides, from the coefficient signs and values of Regression model, variables’ effect on operation unit rate and the scope of the affection may be understood, and furthermore, be fedback to the important variables on improvement and control.
Effective and correct productivity calculation provides not only planning and design units an accurate estimation of costs and schedule but also the basis and reference for construction industry while estimating the teamwork efficiency of a downstream constructor.

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