Design automation and optimization of assembly sequences for complex mechanical systems

Abstract

Assembly sequence design for a mechanical system can have significant impact on manufacturing cost and product quality. Traditionally, such a design process is largely based on experience and best practices, often ineffective and non-optimal as the system becomes complex. This paper proposes a new, systematic method for automatic assembly sequence design and optimization. Key elements include assembly modeling, sequence planning, locating scheme optimization, dimensional quality evaluation, and optimization. First, a directed graph and an assembly matrix are employed to describe the assembly relation of a system. Then, the feasible assembly sequences are generated through layered subassembly detection of adjacency matrices, filtered by engineering constraints. To evaluate quickly the assembly quality and compare the influences of different locating point schemes, a linear 3D variation propagation analysis model with deterministic locating principle is introduced. The optimal locating scheme is then selected using a genetic algorithm with the least variation propagation. Finally, the assembly dimensional quality for different sequences is evaluated and the optimal assembly sequences are achieved through genetic algorithms. A case of automotive body side assembly is presented to illustrate the whole methodology.