隨著工業製程複雜度增加，影響製程表現之品質特性不再只有一種，為同時考量多種品質特性，從而發展出多變量製程能力指標（Multivariate Process Capability Index，MPCI）。目前已有多位學者提出相關多變量製程能力指標，但多假設產品品質特性為常態，然而，許多工業製程之品質特性無法滿足此假設，因此，本研究藉由資料深度（Data Depth）概念說明如何定義製程資料規格區域，進而提出兩個無須分佈假設之多變量製程能力指標。本研究將分別藉由統計模擬及數值實例，評估提出方法的表現及說明如何運用本研究提出之指標來評估製程的表現。

Generally, an industrial product has more than one quality characteristic. In order to establish performance measures for evaluating the capability of a multivariate manufacturing process, several multivariate process capability indices have been developed in the past. Most of the proposed in the literature MPCIs are defined under an assumption, that process quality characteristics are normally distributed. However, this assumption may not hold in practice In this research, based on the data depth concept, we proposed two multivariate process capability indices, which could be used regardless on data distribution. Finally, simulation results show that our proposed indices outperform than existing model. A numerical example further demonstrate the usefulness of the proposed indices.

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