Base shape generation and optimization for multi-axis hybrid additive manufacturing

Abstract

Hybrid additive manufacturing (HAM) processes combine the advantages of both additive and non-AM processing to achieve an improvement on quality, cost, and a good quality-cost balance. The non-additive manufacturing process is able to build the physical component of a computer-aided design model from zero or an existing relatively simple subvolume, called base shape in this paper. Hence, if the processing start point is an existing subvolume, how to determine an optimal base shape to save printing time, avoid manufacturing constraints and ensure component quality is an open question in the process planning. Nevertheless, this topic has rarely been investigated. Therefore, in this paper, we propose an optimization method using model skeleton-based decomposition and evolutionary computation. A set of generic evaluation criteria are defined for alternative evaluation. We also present two case studies in this paper for validating the proposed method and conclude that sequential HAM processes have a wide application potential.