Optimizing Build Orientation for Support Removal using Multi-Axis Machining

TL;DR

This paper introduces a framework for optimizing build orientation in additive manufacturing to facilitate support removal, balancing support volume and accessibility using a novel inaccessibility measure field and automated planning.

Contribution

It presents a new multi-objective optimization approach for build orientation considering support removability and an automated support removal planning algorithm based on the inaccessibility measure field.

Findings

Effective in reducing support volume and improving support accessibility.

Demonstrated success on benchmark 2D and realistic 3D examples.

Provides a systematic method for support removal planning.

Abstract

Parts fabricated by additive manufacturing (AM) are often fabricated first as a near-net shape, a combination of intended nominal geometry and sacrificial support structures, which need to be removed in a subsequent post-processing stage using subtractive manufacturing (SM). In this paper, we present a framework for optimizing the build orientation with respect to removability of support structures. In particular, given a general multi-axis machining setup and sampled build orientations, we define a Pareto-optimality criterion based on the total support volume and the "secluded" support volume defined as the support volume that is not accessible by a given set of machining tools. Since total support volume mainly depends on the build orientation and the secluded volume is dictated by the machining setup, in many cases the two objectives are competing and their trade-off needs to be taken into account. The accessibility analysis relies on the inaccessibility measure field (IMF), which is a continuous field in the Euclidean space that quantifies the inaccessibility of each point given a collection of tools and fixturing devices. The value of IMF at each point indicates the minimum possible volumetric collision between objects in relative motion including the part, fixtures, and the tools, over all possible tool orientations and sharp points on the tool. We also propose an automated support removal planning algorithm based on IMF, where a sequence of actions are provided in terms of the fixturing devices, cutting tools, and tool orientation at each step. In our approach, each step is chosen based on the maximal removable volume to iteratively remove accessible supports. The effectiveness of the proposed approach is demonstrated through benchmark examples in 2D and realistic examples in 3D.