A Novel MILP Model Based on the Topology of a Network Graph for Process Planning in an Intelligent Manufacturing System

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. (C) 2021 THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company.

Automated summary

The intelligent process planning (PP) is an important component in intelligent manufacturing systems, serving as a bridge between product design and actual manufacturing processes. The proposed mixed-integer linear programming (MILP) mathematical model considers network topology structure and OR nodes, effectively solving PP problems and outperforming state-of-the-art algorithms in obtaining optimal solutions.