# Hybrid Manufacturing Process Planning for Arbitrary Part and Tool Shapes

arXiv: https://arxiv.org/abs/2205.11805 · HTML: https://mlsanity.com/paper/2205.11805/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 36 references that are in the map.
- First posted on arXiv 24 May 2022.

## Builds on (most cited first, 3 of 3)

- [Exploring Feasible Design Spaces for Heterogeneous Constraints](https://mlsanity.com/paper/1907.01117/) (2019)
- [Topology Optimization with Accessibility Constraint for Multi-Axis Machining](https://mlsanity.com/paper/2002.07627/) (2020)
- [Automated Process Planning for Hybrid Manufacturing](https://mlsanity.com/paper/1805.07035/) (2018)

## Built on by (most cited first, 1 of 1)

- [Deep Neural Implicit Representation of Accessibility for Multi-Axis Manufacturing](https://mlsanity.com/paper/2409.02115/) (2024)

## Abstract (arXiv)

Hybrid manufacturing (HM) technologies combine additive and subtractive manufacturing (AM/SM) capabilities in multi-modal process plans that leverage the strengths of each. Despite the growing interest in HM technologies, software tools for process planning have not caught up with advances in hardware and typically impose restrictions that limit the design and manufacturing engineers' ability to systematically explore the full design and process planning spaces. We present a general framework for identifying AM/SM actions that make up an HM process plan based on accessibility and support requirements, using morphological operations that allow for arbitrary part and tool geometries to be considered. To take advantage of multi-modality, we define the actions to allow for temporary excessive material deposition or removal, with an understanding that subsequent actions can correct for them, unlike the case in unimodal (AM-only or SM-only) process plans that are monotonic. We use this framework to generate a combinatorial space of valid, potentially non-monotonic, process plans for a given part of arbitrary shape, a collection of AM/SM tools of arbitrary shapes, and a set of relative rotations (fixed for each action) between them, representing build/fixturing directions on 3-axis machines. Finally, we use define a simple objective function quantifying the cost of materials and operating time in terms of deposition/removal volumes and use a search algorithm to explore the exponentially large space of valid process plans to find "cost-optimal" solutions. We demonstrate the effectiveness of our method on 3D examples.