確定性之S curve及不確定性之SS curve均為專案控制而分別被發展出來，但這兩種方法在執行專案控制時均無法避免績效相關性之問題，而SS curve之方法係源自於S curve中較有效之處理過程。然而，本研究發現，SS curve視績效偏差一律源於參數之錯估並據以調整參數的方法，僅適用於實際績效與參數設定不相符合的狀況，因為該方法忽略績效偏差有可能是績效隨機之合理結果，可能會造成對後續專案較為武斷的預估；前述問題之主要原因為SS curve忽略專案績效變動係由因子所引起之事實。因此，本研究利用二維因子狀態模式(Two dimensional factor status model, 2D-FAS)處理因子狀態與循環行為之概念以建立2D-SS curve模擬系統。2D-SS curve可利用因子之隨機變化來模擬造成專案績效之變動，並藉由因子狀態在時間上之延續性來處理績效相關性，適合應用於實際績效與參數設定相符合狀況下之績效相關性處理及專案績效控制。最後，本研究採用一範例專案情境來說明2D-SS curve之有效性及可以彌補SS curve可能產生對績效偏差進行過度修正之問題。

Both certain S curve and uncertain SS curve were developed for the purpose of project control. However, both these two methods could hardly avoid the problem of performance correlation. Although the method of SS curve uses the more effective process which resulted from the method of S curve to dealing with the problem of performance correlation. Nevertheless, as the research found out that SS curve perceives performance deviation as the source of the parameter misestimate, SS curve also adjusts the method of parameter according to the misestimate. Because the method avoided that performance deviation might be the result of performance randomization which could be less neutral for the assessment, SS curve can only be applied when actual performance and the parameter are diverse. The key reason for this problem is that SS curve neglects the fact that the deviation of project performance is resulted from the factors.

This research applied “Two dimensional factor status model (2D-FAS)” which was designed for dealing with both factor state and circle behavior to establish the simulate model. 2D-SS curve utilizes the factors’ randomization changing to simulate the causing changes from project performance and then deal with the performance relevance according to the factor of time lasting. This method is appropriate for the performance relevant procedure and project performance control when the real time performance and the parameter settings are accordant.

Lastly, a project example has been applied in this research to describe the effectiveness of 2D-SS curve and to recover the possible problem that results from the over revising of performance deviation from SS curve.

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