DOE 將工程判斷轉化為統計證據。通過變異數分析（ANOVA），工程師可以量化每個因子的貢獻度，從而做出有信心的工程決策，而非依賴「直覺」。

這是一篇關於 的綜合評述。

在 DOE 的完整工作流中，驗證通常位於最後一環。其核心目的在於：

如果一開始篩選的因子並非真正的關鍵因子，或者因子的水準範圍設定過窄/過寬，DOE 的結果將毫無意義。這被稱為「Garbage In, Garbage Out」。DOE 無法代替工程師的物理直覺，它需要先備知識來選擇正確的變數。

（DOE Verification / Validation）是指在完成實驗設計分析、找出初步最佳參數組合或數學模型後，專門設計並執行額外的實驗，以確認這些預測結果在實際操作中是否真實、可靠且可重複的過程。

Doe verification is a methodology used to verify the accuracy and reliability of experimental designs. It involves using statistical tools and techniques to analyze the relationships between variables, identify significant factors, and optimize experimental conditions. The goal of Doe verification is to ensure that experiments are designed to produce valid and reliable results, minimizing the risk of errors and variability.

教科書上的 DOE 往往假設環境是受控的，但工廠現場的溫度、濕度、原物料批次的變異往往難以控制。若未將這些雜音因子納入實驗設計（如田口方法的外側直交表），驗證結果在實驗室可行，量產時卻會失效。

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.