几乎所有的现代制造过程都属于多工序系统，但现有的质量控制与维护策略联合建模问题多局限于单机系统、失效机制单一等相对简单的生产系统，其成果无法满足多工序系统的现实需求。本项目在揭示多工序质量控制与维护策略耦合机理的基础上，考虑运用半马尔可夫过程—GERT网络进行生产过程建模，以描述多设备间串并联逻辑关系、多生产过程状态以及服从任意分布的设备失效机制，并研究网络参数的配置以及模型求解问题，以获取后续联合建模的成本期望与时间期望；然后，结合统计、经济等方面的约束，研究多工序制造过程质量控制与维护策略联合建模与求解问题；考虑到生产过程数据不断更新，故根据新数据的反馈，设计一套多工序质量控制与维护策略集成模型的修正机制，以获得最佳的联合策略。本项目不仅能丰富统计过程控制与维护决策领域的理论与方法，更能为多工序制造过程质量控制与维护策略的联合决策提供一种整体解决方案，具有重要的现实意义。

Almost all of modern manufacturing processes belong to multi-stage systems, but the existing joint modeling of quality control and maintenance policy is limited to the relatively simple production system with a single machine supposed to have a type of failure mechanism, as a result, it cannot serve the multi-stage manufacturing process well. First the coupling mechanism of quality control and maintenance of the multi-stage manufacturing process is revealed. Based on this, a semi-Markov process method—GERT network is used to model the production system in order to describe the series-parallel logic, multistate and the failure mechanism following any distribution. Then the configuration of the network parameters and the solution of the model are studied to get the expected cost and expected time for the subsequent joint modeling. Next combing with statistical constraints and economic constraints, the joint modeling of quality control and maintenance policy for the multi-stage manufacturing process is presented. due to the continuously updating data in the production process, a model correction mechanism is designed to obtain the optimal strategies. This project can not only enrich the theory and methods in the fields of statistical process control and maintenance decision, but also provide a whole solution for the joint decision of quality control and maintenance for the multi-stage manufacturing process, which has important practical significance.