在工程研發與製造領域中，DOE（Design of Experiments，實驗設計）不僅僅是一種統計工具，更是一種解決問題的邏輯思維。這篇評述將從定義、核心價值、執行挑戰及未來趨勢四個維度進行剖析。
Doe verification is a powerful statistical technique used to optimize and validate experimental designs. By following the key steps outlined above, experimenters can ensure that their experiments are designed to produce reliable and accurate results, minimizing the risk of errors and variability. With its wide range of applications across various industries, Doe verification is an essential tool for anyone involved in experimental design and analysis.
：檢驗統計模型（如回歸方程）的預測值與實際測得值是否吻合。
隨著工業 4.0 與 AI 的發展，DOE 正在與大數據分析結合。傳統 DOE 是「小數據」分析（樣本少但精準），而現代機器學習傾向「大數據」。未來的 DOE 將更多地與 虛擬仿真 結合，在數位孿生環境中進行大規模虛擬實驗，再進行實體驗證，這將進一步降低驗證成本。