# Tool Run-Out in Micro-Milling: Development of an Analytical Model Based on Cutting Force Signal Analysis

## TL;DR

This paper introduces a new analytical model to predict tool run-out in micro-milling using cutting force signals, avoiding the need for time-consuming measurements.

## Contribution

The novel contribution is a method to calibrate model parameters using cutting force signal analysis, eliminating the need for dimensional measurements.

## Key findings

- The proposed model is based on cutting force signal analysis for predicting tool run-out in micro-milling.
- The method was tested on additively manufactured AlSi10Mg specimens and showed promising results.
- The approach has a strong mathematical foundation and potential for future development.

## Abstract

Micro-machining is a widespread finishing process for fabricating accurate parts as biomedical devices. The continuous effort in reducing the gap between the micro- and macro-domains is connected to the transition from conventional to micro-scale machining. This process generates several undesired issues, which complicate the process’s optimization, and tool run-out is one of the most difficult phenomena to experimentally investigate. This work focuses on its analytical description; in particular, a new method to calibrate the model parameters based on cutting force signal elaboration is described. Today, run-out prevision requires time-consuming geometrical measurements, and the main aim of our innovative model is to make the analysis completely free from dimensional measurements. The procedure was tested on data extrapolated from the micro-machining of additively manufactured AlSi10Mg specimens. The strategy appears promising because it is built on a strong mathematical basis, and it may be developed in further studies.