本研究將灰關聯分析與反應曲面法結合D2MAIC,幫助使用者以數據計算的方式發掘關鍵因子,進行參數的優化,以降低人為判斷可能造成的失誤。利用CNC實驗對此模型進行驗證,以表面粗糙度作為品質特性衡量指標,期望降低加工之表面粗糙度,依據結果顯示,經此模式改善後,表面粗糙度改善幅度達50%,證明其可行性。
This research integrated Grey Relational Analysis and Response Surface Methodology with D2MAIC. Users can select critical parameters to optimize process with data calculation and reduce the percentage of human error. In order to verify this model, this research took a CNC experiment and defined the surface roughness value as the index of quality. It looks forward to reducing the surface roughness value. According to the result, the surface roughness value has improved 50%. The result has confirmed the feasibility.