Maps of Dipersions for Machining Processes

TL;DR

This paper introduces a method to model machining process dispersions by integrating geometrical specifications and expert knowledge into know-how maps, enhancing process understanding and control.

Contribution

It proposes a novel approach to represent turning dispersions using know-how maps that include both explicit and tacit knowledge, validated through experimental study.

Findings

Knowledge maps effectively model machining dispersions.

Inclusion of expert experience improves process understanding.

Experimental validation on HES 300 machine confirms approach's usefulness.

Abstract

During the products design, the design office defines dimensional and geometrical parameters according to the use criteria and the product functionality. The manufacturing department must integrate the manufacturing and the workpiece position dispersions during the choice of tools and machines operating modes and parameters values to respect the functional constraints. In this paper, we suggest to model the turning dispersions taking into account not only geometrical specifications of position or orientation but also the experience of method actors. A representation using the principle of know-how maps in two or three dimensions is privileged. The most interesting aspect is that these maps include tacit and explicit knowledge. An experimental study realized on a machine tool (HES 300) allows to elaborate knowledge maps especially for the turning process.