Parametric shape optimization for combined additive-subtractive manufacturing

TL;DR

This paper presents a parametric shape optimization method for combined additive and subtractive manufacturing, aiming to minimize machining and material costs while maintaining quality, using surrogate models for efficiency.

Contribution

It introduces a novel numerical methodology with surrogate-based optimization for reducing extra material and machining in combined manufacturing processes.

Findings

Effective reduction in manufacturing costs demonstrated

Surrogate models improve computational efficiency

Enhanced part quality with optimized inner structures

Abstract

In the industrial practice, additive manufacturing processes are often followed by post-processing operations such as subtractive machining, milling, etc. to achieve the desired surface quality and dimensional accuracy. Hence, a given part must be 3D printed with extra material to enable such finishing phase. This combined additive/subtractive technique can be optimized to reduce manufacturing costs by saving printing time and reducing material and energy usage. In this work, a numerical methodology based on parametric shape optimization is proposed for optimizing the thickness of the extra material, allowing for minimal machining operations while ensuring the finishing requirements. Moreover, the proposed approach is complemented by a novel algorithm for generating inner structures leading to reduced distortion and improved weight reduction. The computational effort induced by classical constrained optimization methods is alleviated by replacing both the objective and constraint functions by their sparse-grid surrogates. Numerical results showcase the effectiveness of the proposed approach.