# Automated Process Planning for Turning: A Feature-Free Approach

**Authors:** Morad Behandish, Saigopal Nelaturi, Chaman Singh Verma, Mats Allard

arXiv: 1905.09434 · 2019-07-03

## TL;DR

This paper introduces a feature-free process planning method for turning operations that enhances CNC machining by enabling seamless integration with milling planning, especially for complex shapes without relying on feature separation.

## Contribution

The paper extends a feature-free planning approach from milling to turning, allowing for integrated, complex shape handling without feature-based analysis.

## Key findings

- Successful implementation of feature-free turning planning
- Enables integration with mill-turn process planning
- Handles complex shapes without feature semantics

## Abstract

Turning is the most commonly available and least expensive machining operation, in terms of both machine-hour rates and tool insert prices. A practical CNC process planner has to maximize the utilization of turning, not only to attain precision requirements for turnable surfaces, but also to minimize the machining cost, while non-turnable features can be left for other processes such as milling. Most existing methods rely on separation of surface features and lack guarantees when analyzing complex parts with interacting features. In a previous study, we demonstrated successful implementation of a feature-free milling process planner based on configuration space methods used for spatial reasoning and AI search for planning. This paper extends the feature-free method to include turning process planning. It opens up the opportunity for seamless integration of turning actions into a mill-turn process planner that can handle arbitrarily complex shapes with or without a priori knowledge of feature semantics.

## Full text

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## Figures

11 figures with captions in the complete paper: https://tomesphere.com/paper/1905.09434/full.md

## References

45 references — full list in the complete paper: https://tomesphere.com/paper/1905.09434/full.md

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Source: https://tomesphere.com/paper/1905.09434