中文摘要：

针对制造过程中的多因素工序质量诊断问题，提出一种基于二分法的工序质量诊断算法。通过对质量因素集合逐次进行折半划分，构造质量因素集合的完全二叉树结构，以完全二叉树中每一节点对应的质量因素子集合为非控因素，构建父节点对应的中间质量指标关于选定非控因素集合的选控图，构成多因素工序质量诊断体系。在对异常质量因素进行诊断时，通过比较具有相同父节点的两个子节点所对应的选控图，逐次缩小异常因素所在的范围，直至确定具体的异常质量因素。理论分析和应用表明，基于二分法的多因素工序质量诊断算法可以使异常因素的诊断过程与调整过程相互独立，并能有效缩短确定异常质量因素时对选控图进行比较的次数，提高诊断效率。

英文摘要：

Aiming at the problem of multi-cause process quality diagnosis in manufacturing, an algorithm based on dichotomy is proposed. Quality cause set is divided by degrees to build its complete binary tree, and then every node in the complete binary tree is selected as non-control cause set to construct cause-selecting control chart of the intermediate quality index in its parent node. In quality diagnosis, control charts with same parent are compared to determine the scope of the abnormal quality causes until they are affirmed. Theoretical analysis and practice prove that the diagnosis algorithm based on dichotomy could make the procedure of quality diagnosis independent to the adjustment procedure, and the steps of control charts comparison can be reduced greatly, so the efficiency of diagnosis is highly improved.