Machining with minimum quantity lubrication (MQL) has been the focus of many scientific investigations since the last 20 years. Nevertheless an acceptable method of predicting the thermal influences on the workpiece quality has still not been developed. This paper describes a simulation approach to estimate the distribution of the cutting energy during machining. During machining, the cutting power is measured to calculate the specific cutting power for each machining process – here drilling, tapping and milling of aluminum. In parallel, the warm-up of the part is measured by fast response thermocouples implanted closed of the machined zone. These thermocouples identify the cutting energy entering into the work piece

BOYER, Henri-François

KOPPKA, Frank

LORONG, Philippe

RANC, Nicolas

English

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Henri-François BOYER, Frank KOPPKA, Nicolas RANC, Philippe LORONG - Identification of the
heat input during dry or MQL machining - In: 9th International Conference of High Speed
Machining  - HSM 2012, Espagne, 2012-03-07 - Conference of High Speed Machining - 2012
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Identification of the heat input during dry or MQL machining 
HF. Boyer1,2, Frank Koppka2, N. Ranc1, P. Lorong1 
1Arts et Metiers ParisTech, CNRS, PIMM, 151, Bd de l’Hôpital, 75013 Paris, France 
2Renault – Powertrain Process Engineering Division, FRCTRB02130, 67, rue des Bons Raisins, 92500 Rueil-
Malmaison, France  
  
 
        
Abstract 
Machining with minimum quantity lubrication (MQL) has been the focus of many scientific investigations since 
the last 20 years. Nevertheless an acceptable method of predicting the thermal influences on the workpiece 
quality has still not been developed. This paper describes a simulation approach to estimate the distribution 
of the cutting energy during machining. During machining, the cutting power is measured to calculate the 
specific cutting power for each machining process – here drilling, tapping and milling of aluminum. In parallel, 
the warm-up of the part is measured by fast response thermocouples implanted closed of the machined zone. 
These thermocouples identify the cutting energy entering into the work piece. 
 
Keywords:  
Machining, Heat transfer, Finite Element Method (FEM) 
 
 
1 INTRODUCTION 
Machining with minimum quantity lubrication (MQL) [1] 
has been the focus of many scientific investigations since 
the last 20 years. The technology has been optimized and 
is nowadays widely used in machining industry. 
Nevertheless an acceptable method of predicting the 
thermal influences on the work piece quality has still not 
been developed. 
The lack of cutting fluid in dry or MQL machining 
provokes local warm-ups of the part. These temperature 
rises deform the work piece in an inhomogeneous way 
during its manufacturing which can cause quality 
problems, depending of the size of tolerances. With the 
help of FEM simulations using an estimation of the heat 
flow for each cutting process, these local warm-ups can 
be easily identified.  
This paper describes a method to identify, with part 
temperature measurement during machining, intensity of 
the heat flux going to the part. Originality of this method is 
in determination of measuring point position with shape 
criteria on temperature curves. It allows avoiding errors 
links to measuring point position into part. In a second 
part, thermo-mechanical distortions of an aluminum 
(AS9U3) clutch case during manufacturing are simulated. 
 
2 STATE OF THE ART 
Generally, authors consider that about 90% to 100% of 
energy associated with chip formation is converted to 
heat during machining. Figure 1 illustrates the five heat 
sources that could be observed during machining. 
1. Plastic strain in primary shear zone 
2. Friction between tool and chip 
3. Plastic strain in secondary shear zone 
4. Plastic strain in tertiary shear zone 
5. Friction between tool and part 
Heat created in these zones is distributed between tool 
(Qt), chip (Qc), work piece (Qp) and environment (Qe). In 
first approximation three main heat sources are 
distinguished:  plastic strain of chips (Qcc), friction on rake 
face (Qfc) and friction on flank face (Qfd), Figure 2. 
Main part of the cutting energy is going to chips, tool and 
work piece; heat going to environment is unimportant. 
 
 
Figure 1: Heat sources during machining [2,3] 
Fleischer et al. [4] made an extensive literary research to 
precise repartition of the cutting energy during dry or MQL 
machining (Table 1). Heat input into work piece varies 
between 1 to 35 % of the cutting energy depending of 
process studied. 
 
 
Figure 2: Heat sources and distribution during machining 
Authors developed two different approaches to identify 
heat flow going into part during machining. On first hand, 
authors’ aim is to identify partition of the cutting power 
going into part [5-10]. On the other hand, authors directly 
identify heat input as a function of cutting speeds and tool 
geometry [2-4,11-14]. The literary research shows that 
heat input into work piece is dependant of many factors: 
work piece material, machinability, tool geometry and 
material, cutting conditions, etc. All these method are 
based on temperature measurement of parts during 
machining. 
 
Table 1: Distribution of the cutting energy during 
machining [3] 
Davies et al. [14] propose a comparison between different 
measurement methods of temperature in material 
removal processes (Table 2). According to their study, a 
method based on thermocouple was chose for its thermal 
and time resolution properties and its for cost and easy of 
set up reason. 
3 OBJECTIVES 
Main objective of this paper is to propose an identification 
method for heat flow going to part during manufacturing. 
This method is an inverse method based on FEM 
simulations with a unit heat flow and measurement of 
temperature rise (with a thermocouple) into parts during 
machining. Originality of this method is reconstruction of 
thermocouple position with temperature curve shape. 
Heat flow will be identified as a part of the cutting energy. 
4 EXPERIMENTAL SETUP 
4.1 Power consumption 
Cutting energy is estimated using spindle power 
consumption. A wattmeter is plugged to measure 
instantaneous spindle electric consumption. Only cutting 
energy is considered, energy needed for tool 
displacement is not considered (weak compared to 
cutting energy). 
4.2 Temperature measurement 
For temperature measurements, fast response 
thermocouples (type K) are inserted into parts near the 
machined zone (distance lower than 2 millimeters). 
Position of thermocouple is choose near machined zone 
to increase precision of heat flow identification. 
 
 
Figure 3: Parts geometry used for heat flow identification 
4.3 Parts geometry 
Figure 3 shows dimension of machined parts. Two parts 
where designed: first one for milling tests and second one 
for drilling and tapping tests. Three drills for thermocouple 
are done in each part to insert thermocouple. Direction of 
drilling is orthogonal to heat flow vector to minimize 
perturbation of thermal fields by drilling geometry. 
5 FEM SIMULATIONS 
5.1 Principe 
Commercial FEM code does not allow imposing mobile 
heat flow representative of tool movements directly. To 
avoid this problem, strips are cut off into machined 
surface using direction of tool displacement. Figure 4 
illustrates, for cylindrical (drilling, reaming, tapping) and 
plane surfaces, method of machined surface cutting. 
 
 
Figure 4: Stripping of machined surface 
 
Heat flow is successively imposed on each strip. For 
continuity reasons, heat flow is imposed in three times on 
each strip: first a growing heat flow, then a constant heat 
flow and last a decreasing heat flow (Figure 5). Different 
strategies were tested for increasing and decreasing heat 
flows (discontinuous, linear, polynomial). FEM simulation 
shows that continuity of heat flow is important but that 
strategies for increasing and decreasing have no effects 
on results. 
Length of strips is a compromise between having a 
continuous response of the model and having an 
acceptable calculation time.  
 
Figure 5: Heat flow put on each strip for FEM simulations 
5.2 Hypothesis 
Influence of conductivity with fixture and convection with 
environment 
In heat transfer analysis, thermal diffusivity (D) is the 
thermal conductivity divided by density (ρ) and specific 
heat capacity (c). 
 
 A thermal characteristic time could be defined using 
thermal diffusivity D and a length L. This characteristic 
time is duration needed to transmit a temperature signal 
over length L. Table 3 shows for classical, automotive 
materials, orders of magnitude for thermal characteristic 
time. 
  
In first seconds of simulation, affected zone by heat flow is 
thin (a few centimeters). If fixture is far from imposed heat 
flow, heat conduction to fixture could be neglected. 
Heat convection is not taken into account because of 
short duration of analysis. 
 Drilling Turning Milling 
Tool 5 – 15% 2.1 – 18% 5.3 – 10% 
Work piece 10 – 35% 1.1 – 20% 1,3 – 25% 
Chip 55 – 75% 1.3 – 25% 65 – 74,6% 
Tool	  displacement	  
Milling	   Drilling	  /	  Reaming	  /	  Tapping	  
 Tool	  displacement	  
Influence of errors on thermal material properties 
Model sensibility about error on thermal conductivity and 
thermal capacity (ρ.c) were studied with FEM simulations. 
On the first hand, an error on thermal conductivity of +/-
10% links to an error of 10% on response model. On the 
other hand, error on thermal conductivity is less 
important: variation of +/-10% of conductivity links to an 
error of 2%. Thermal conductivity of material studied must 
be correctly estimated to reduce errors on heat flow 
identification. 
Influence of drilling for thermocouple 
Simulation shows a great influence of thermocouple 
drilling into part on thermal fields. To identify precisely 
heat flow during machining, simulations have to be done 
with drilled parts (correct diameters and length). 
5.3 Results of FEM simulations 
Simulations were conducted using FEM code Abaqus©.  
A preprocessor was written to automate data converting, 
computing processes, and data extraction from results of 
analysis. 
Figure 6 presents an example of results for simulation of 
a unit mobile heat flow on a plane (milling case at feed 
speed 20 m/min). Length between heated surface and 
measurement nodes influence temperature and shape of 
temperature curve. These two data will be used to identify 
position of thermocouple during machining and heat flow 
into part due to machining. 
6 INVERSE IDENTIFICATION METHOD 
For a speed of the moving heat flow and at one point of 
the part, maximum simulated temperature depends on 
heat flow put on the machined surface and distance 
between measuring point and machined surface. 
6.1 Thermocouple position 
Position of thermocouple is identified using a shape 
criteria on temperature curve. Precision of the method is 
directly linked to number of node in the measurement 
area. This parameter is controlled by user when part is 
meshed. 
In first step, a unit heat flow is used to simulate 
temperature in part for different positions of 
thermocouple. These simulations are done using different 
mesh: each one correspond to one position of 
thermocouple. Temperature curves for thermocouple are 
extracted of FEM results.  
During second step, temperature curve are normalized 
with maximum temperature (Figure 7). Shapes of curve 
are different for each position of thermocouple. When 
distance between machined surface and thermocouple 
increase, expand of temperature curve is observed. 
A least-square method is used to identify witch two 
simulated temperature curves are most looking to 
measured curve. An upper and lower position of 
thermocouple is estimated: precision is linked to number 
of simulation done.  
For a position of thermocouple, maximum simulated 
temperature at thermocouple position is proportional to 
intensity of heat flow. Using positions determined 
previously, intensity is estimated. 
 
 
Figure 6: Example of result for a unit heat flow moving on 
a plane at 20 m/s (milling case) 
 
Figure 8 describes evolution of maximum temperature 
obtained by simulation for a unit mobile heat flow in 
function of distance to machined surface. For a good 
precision of maximum measured temperature, 
thermocouples have to be in first millimeters under 
machined surface. Along two first millimeters, maximum 
temperature is proportional to distance. An error of n% on 
estimation of thermocouple position pull to an error of n% 
to heat flow estimation. 
 
Figure 7: Normalized temperature curves for same node 
as figure 6 
 
Thermal characteristic time (s)  Thermal 
conductivity 
W / (m.K) 
Density 
Specific heat 
capacity 
J / (Kg.K) 
Thermal 
diffusivity 
m² / s L = 1 cm L = 1 mm 
Aluminium (AS9U3) 237 2,7 945 9,29.10-5 1,08 1,08.10-2 
Cast Iron (GL09) 100 7,2 550 2,53.10-5 3,96 3,96.10-2 
Steel 46 7,8 500 1,18.10-5 8,48 8,48.10-2 
Table 2: Orders of magnitude of thermal characteristic for classical automotive materials 
 
Figure 8: Evolution of maximum temperature obtained by 
simulation with distance from machining surface (milling 
case, unit mobile heat flow at 20 m/s) 
6.2 Heat flow identification 
Heat flow is proportional to maximum temperature 
observed. Upper and lower position of thermocouple 
identified with shape criteria is used to determine an 
estimation of heat flow during machining. 
Cutting speed 
(m/min) 
Feed rate 
(mm/th) 
Cutting width 
(mm) Milling 
2 000 
3 000 
4 000 
0.1 
0.15 
0.2 
1 
2 
Tool diameter 
(mm) 
Cutting speed 
(m/min) 
Feed Rate 
(mm/tr) Drilling 
5 
6.75 
8 
200 
300 
400 
0.1 
0.2 
Tool diameter 
and pitch 
Cutting speed 
(m/min) Tapping 
M6x1 
M8x1.25 
M10x1.5 
40 
60 
80 
Table 3: Cutting conditions for milling, drilling and tapping 
tests 
7 CONCLUSION 
This paper describes a method to identify heat flow going 
into part during milling, drilling and tapping. Originality of 
this method is to avoid errors links to estimation of 
thermocouple position.  
This method will be used to identify heat flow going into 
part during milling, drilling and tapping of aluminum alloy 
(AS9U3). Goal of the study is to be able to predict 
temperature rise and mechanical distortions of an 
aluminum clutch case. 
Table 3 precise cutting conditions that would be tested for 
milling, drilling and tapping. These cutting conditions are 
representative of those used in automotive industry for 
machining of aluminum parts. Tools are also chose to be 
representative of automotive machining: drills and tap 
drills are carbide tools. Milling tool has four PCD tool 
(diameter 63mm).   
FEM simulation of thermal distortions during machining 
will help manufacturer to chose to do (or not) cooling of 
parts or thermal compensation during machining or will 
help them to reorganize plan of procedure to minimize 
distortions during manufacturing. 
8 ACKNOWLEDGMENTS 
This paper presents work funded by the French agency 
for environment and energy consumption (ADEME) – 
Project Alusisec. Aim of this project is to study dry and 
MQL machining for automotive parts. 
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Identification of the heat input during dry or MQL machining

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Identification of the heat input during dry or MQL machining

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