Dry or MQL machining : quantification and consideration of thermal distortions along the process

The application of MQL or dry machining in mass production becomes more and more accepted. Dry (MQL) machining is a very efficient solution to reduce the usage of cutting fluids and represents an effective measure for an environmental friendly production. However, these techniques do not benefit any more from the stabilization in temperature obtained with cutting fluids. More important and more heterogeneous increases of the temperature are observed. This leads to distortions of the work piece during machining which are necessary to be taken into account to maintain the geometrical quality of the manufactured surfaces.A model of the warm-up of a part during machining is presented. The obtained model allows to quantify heat introduced into the work piece for simple operations and to feign the distortions of a complex part when operations are enchained. This quantification is based on an inverse method. It is applied for reaming, drilling and tapping process for an aluminum alloy AS9U3. Secondly, a study about influence of operations organization is done. We use the model to quantify distortions an aluminum clutch case along machining. This study illustrates interest of the model and of tools developed during the PhD. In a last part, economic and environmental stakes of the MQL approach are discussed.

Data and Resources

Additional Info

Field Value
Source https://pastel.hal.science/pastel-00936121
Author Boyer, Henri-Francois
Maintainer CCSD
Last Updated May 7, 2026, 06:32 (UTC)
Created May 7, 2026, 06:32 (UTC)
Identifier NNT: 2013ENAM0018
Language fr
Rights https://about.hal.science/hal-authorisation-v1/
contributor Laboratoire Procédés et Ingénierie en Mécanique et Matériaux (PIMM) ; Conservatoire National des Arts et Métiers [Cnam] (Cnam)-Centre National de la Recherche Scientifique (CNRS)-Arts et Métiers Sciences et Technologies
creator Boyer, Henri-Francois
date 2013-06-12T00:00:00
harvest_object_id cb7fba02-a19c-40da-aa18-2f812445dddd
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2026-03-31T00:00:00
set_spec type:THESE