Intelligent process planning (PP) is one of the most important components in an intelligent manufacturing system and acts as a bridge between product designing and practical manufacturing. PP is a nondeterministic polynomial-time (NP)-hard problem and, as existing mathematical models are not formulated in linear forms, they cannot be solved well to achieve exact solutions for PP problems. This paper proposes a novel mixed-integer linear programming (MILP) mathematical model by considering the network topology structure and the OR nodes that represent a type of OR logic inside the network. Precedence relationships between operations are discussed by raising three types of precedence relationship matrices. Furthermore, the proposed model can be programmed in commonly-used mathematical programming solvers, such as CPLEX, Gurobi, and so forth, to search for optimal solutions for most open problems. To verify the effectiveness and generality of the proposed model, five groups of numerical experiments are conducted on well-known benchmarks. The results show that the proposed model can solve PP problems effectively and can obtain better solutions than those obtained by the state-of-the-art algorithms.

智能工艺规划（PP）是智能制造系统中最重要的组成部分之一，是产品设计和实际制造之间的桥梁。PP 是一个非确定性多项式时间 (NP) 难题，并且由于现有数学模型不是以线性形式表述的，因此无法很好地求解它们以实现 PP 问题的精确解。本文通过考虑网络拓扑结构和代表网络内部一种 OR 逻辑的 OR 节点，提出了一种新颖的混合整数线性规划 (MILP) 数学模型。通过提出三种类型的优先关系矩阵来讨论操作之间的优先关系。此外，所提出的模型可以在常用的数学规划求解器中进行编程，例如 CPLEX、Gurobi 等，为大多数开放问题寻找最佳解决方案。为了验证所提出模型的有效性和通用性，在众所周知的基准上进行了五组数值实验。结果表明，所提出的模型可以有效地解决PP问题，并且能够获得比最先进算法获得的更好的解决方案。