Metal machining is one of the most important manufacturing processes in today’s pro-
duction sector. The tools used in machining have been developed over the years to improve their
performance, by reducing the cutting forces, the friction coefficient, and the heat generated during the
cutting process. Several cooling systems have emerged as an effective way to remove the excessive
heat generated from the chip-tool contact region. In recent years, the introduction of nano and
micro-textures on the surface of tools has allowed to further improve their overall performance.
However, there is not sufficient scientific data to clearly show how surface texturing can contribute
to the reduction of tool temperature and identify its mechanisms. Therefore, this work proposes an
experimental setup to study the tool surface characteristics’ impact on the heat transfer rate from the
tools’ surface to the cooling fluid. Firstly, a numerical model is developed to mimic the heat energy
flow from the tool. Next, the design variables were adjusted to get a linear system response and to
achieve a fast steady-state thermal condition. Finally, the experimental device was implemented
based on the optimized numerical model. A good agreement was obtained between the experimental
tests and numerical simulations, validating the concept and the implementation of the experimental
setup. A square grid pattern of 100 μm × 100 μm with grooves depths of 50, 100, and 150 μm was
introduced on cutting insert surfaces by laser ablation. The experimental results show that there is a
linear increase in heat transfer rate with the depth of the grooves relatively to a standard surface, with
an increase of 3.77% for the depth of 150 μm. This is associated with the increase of the contact area
with the coolant, the generation of greater fluid turbulence near the surface, and the enhancement of
the surface wettability.
This work was supported by FCT (Fundação para a Ciência e a Tecnologia) through the
grant 2020.07155.BD and by the project POCI-01-0145-FEDER-030353 (SMARTCUT). Additionally,
this work was supported by FCT national funds, under the national support to R&D units grant,
through the reference projects UIDB/04436/2020 and UIDP/04436/2020.
The authors truly acknowledge the funding provided by the projects POCI-01-
0145-FEDER-030353 (SMARTCUT). To Palbit S.A., for providing the cutting inserts essential for the
experimental tests
