Most manufacturing industries produce products through a series of sequential stages, known as a multistage process. In a multistage process, each stage affects the stage that follows, and the process often has multiple response variables. In this paper, we suggest a new procedure for optimizing a multistage process with multiple response variables. Our method searches for an optimal setting of input variables directly from operational data according to a patient rule induction method (PRIM) to maximize a desirability function, to which multiple response variables are converted. The proposed method is explained by a step‐by‐step procedure using a steel manufacturing process as an example. The results of the steel manufacturing process optimization show that the proposed method finds the optimal settings of input variables and outperforms the other PRIM‐based methods.

中文翻译：

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使用患者规则归纳法对多阶段制造过程进行多响应优化

大多数制造业通过一系列连续的阶段来生产产品，这些阶段称为多阶段过程。在多阶段过程中，每个阶段都会影响随后的阶段，并且该过程通常具有多个响应变量。在本文中，我们建议了一种用于优化具有多个响应变量的多阶段过程的新过程。我们的方法根据患者规则归纳法（PRIM）直接从操作数据中搜索输入变量的最佳设置，以最大化期望函数，将多个响应变量转换为该函数。通过以钢制造过程为例的分步过程对提出的方法进行了说明。