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\chapter{Conclusions and Recommendations} \label{chap:conclus_recommen}

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Since the main objective of the present thesis was the understanding of the
generation mechanisms of acoustic emission (AE) during the course of metal cutting,
four sets of metal cutting tests (Tests~I--IV) were accomplished for four different
work materials (two carbon steels 080A15 and 080M40, a stainless steel 304S15, and an
aluminium \mbox{6082-T6}), during which AE and also other signals (cutting forces,
vibration, and temperature) were acquired: during Test~I, the cutting conditions were
varied over a wide range, i.e.\ cutting speed ($V$), 50--300~m$/$min, feed rate
($t_1$), 0.01--0.2~mm$/$rev, and width of cut ($w$), 0.1--2.4~mm; during Test~II, the
feed rate was quasi-continuously varied from 0.24~mm$/$rev down to the very low value
0.005~mm$/$rev; during Test~III, the width of cut was continuously varied in the
0--3~mm range; finally, during Test~IV, the work material was preheated, so that
cutting was performed with different initial workpiece temperatures ($T_\mr{W}$).
Good agreement was obtained between Test~I data and experimental results from
published material.

According to many authors~\cite{kannatey-asibu81,moriwaki83,li02}, continuous-type AE
is thought to be generated due to plastic deformation during metal cutting with
continuous chip formation, without BUE, and with a perfectly sharp tool; however,
during metal cutting, since phenomena that lead to unwanted AE bursts can not be
completely unavoidable, a technique that calculates the power of AE ($I_\mr{power}$)
without taking into the calculation the random burst-type emissions, named as AE mode
($I_\mr{mode}$)~\cite{blum90}, was utilized as a representation of the energy content
of continuous AE ($I_\mr{power} = I_\mr{mode}^2$). Furthermore, a technique which
indicates the frequency value that divides the AE power spectrum into two parts of
equal energy, called mean frequency ($f_\mr{mean}$)~\cite{rangwala91b}, was utilized
as a representation of the frequency content of AE.

Since, as proposed, AE is generated due plastic deformation during metal cutting, a
technique that predicts basic metal cutting parameters, such as strain, strain rate,
flow stress, and temperature, developed by Oxley and co-workers~\cite{oxley89}, was
employed, so that more knowledge of the cutting process could be achieved, and,
therefore, any potential relationship between the AE signals and the parameters
governing plastic deformations could be assessed. However, since, at present, Oxley's
model can only simulate metal cutting of carbon steel work materials, only
predictions for the work materials 080A15 and 080M40 could be obtained.

To put it briefly, in Chapter~\ref{chap:review} (and also
Appendices~\ref{chap:oxley}--\ref{chap:finite_diff}), the necessary theory on the
subject of metal cutting and AE was thoroughly discussed, and together with the
experimental results presented in Chapter~\ref{chap:results} (Test~I--IV), these
results were analysed in Chapter~\ref{chap:discuss}, and the mechanism of AE
generation were thoroughly discussed, resulting in the conclusions that are
summarized in the following section; besides, in the section after the next, some
recommendations for further work are also presented.


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\section{Conclusions} \label{sec:conclus}

This section presents a summary of the conclusions arrived at throughout the present
thesis:
\begin{itemize}

   \item Test~I results showed that $I_\mr{power}$ increases with $V$ and decreases
   with $t_1$, according to the approximate relationship $I_\mr{power} \propto
   V^{n_1}t_1^{n_2}$, where $n_1$ and $n_2$ are work material dependent; index $n_1$
   was found to be between $3.7$ and $4.6$, and $n_2$ between $-0.63$ and $-0.01$.
   Moreover, $I_\mr{power}$ was observed to increase with $w$, but  with decreasing
   rate of increase, so that $I_\mr{power}$ tends to a constant value for high $w$
   values. In the frequency domain, although very scattered, $f_\mr{mean}$ was
   observed to decrease with $V$ and to remain more or less unchanged with $t_1$ and
   $w$.

   \item Test~II and~III AE data were observed to be very scattered, which was attributed
   to the small length of the acquired data sets (approximately 10~ms). In order to remove
   the unwanted effect of burst-type AE in the computation of the AE mode, data sets
   longer than 100~ms must be acquired.

   \item Test~III results showed that when high vibrations are present, named as chatter,
   the resulting AE signal is highly affected by these vibrations (the level of
   $I_\mr{power}$ was observed to increase up to 20 times on the onset of chatter).

   \item According to Test~IV results, $I_\mr{power}$ was observed to decrease with
   increasing workpiece temperature $T_\mr{W}$.

   \item Since most published
   models~\cite{dornfeld80,kannatey-asibu81,schmenk84,blum90,rangwala91a,saini96} relate
   $I_\mr{power}$ to cutting power $\dot{U}$, according to the proportion $I_\mr{power}
   \propto \dot{U}$, this relationship was investigated by using Test~I results. It was
   concluded that this relationship was only observed if the only cutting condition
   that was allowed to change was $V$, and $t_1$ and $w$ were kept constant, which was the
   case of the experimental procedure used to derive most published models. Even so, if
   only $V$ was changed, Test~I AE data seemed to hold a relationship of the type
   $I_\mr{power} \propto \dot{U}^n$, where $n > 1$.

   \item The finite-difference technique was employed in order to determine the
   relationship between the tool-chip interface temperature ($T_\mr{int}$) and the
   temperature measure by the two thermocouple ($T_1$ and $T_2$) placed some distance
   below the tool-chip interface. For a given value of $T_\mr{int}$, $T_2$ was
   predicted to be lower than $T_2$, as expected, since $T_2$ was measure further from the
   tool-chip interface, and $T_1$ and $T_2$ were predicted to increase with increasing $w$ and
   $l_\mr{int}$. As predictable, $T_1$ and $T_2$ were found to increase with
   $T_\mr{int}$. Moreover, since $T_1$ and $T_2$ are dependent on $l_\mr{int}$, and
   $l_\mr{int}$ is dependent on the cutting process and not known in advance, this makes
   practical the predictions of $T_\mr{int}$ from measurements of $T_1$ and $T_2$ rather
   difficult.

   \item In order to access the accuracy of Oxley's model to predict metal cutting
   parameters, the experimental cutting force and temperature results from Test~I and
   also temperature results from Test~IV were used to be compared against predictive values of
   forces and temperatures from Oxley's model. A fairly good agreement was observed between
   predictive and experimental results, but for the lowest values of $V$ and $t_1$, the
   experimental cutting force results were observed to be bellow predictions; this was
   attributed to the onset of built-up edge (BUE), since BUE tends to reduce the cutting
   forces.

   \item In order to investigate the typical relationship observed between $I_\mr{power}$
   and $w$ ($I_\mr{power}$ increases with $w$, but its rate of increase decreases
   with $w$) shown by Test~I results and also by published
   results~\cite{lan85,messaritis86,inasaki81,lan86,blum90}, a very simple model for
   AE generation and propagation was developed. It was concluded that as $w$
   increases, and the AE events are generated further apart, some AE waves will
   travel longer distances than others to a remote AE sensor, resulting in a
   difference in phase delay for different arriving waves. Consequently, due to the
   effect of phase attenuation, the resultant AE signal at the sensor will not
   increase proportionally to the increase of AE activity at the generation source,
   when the volume of deformation increases due to increasing $w$.

   \item Since it was demonstrated that Oxley's theory can be used to model the cutting
   process rather accurately, it was decided to use Oxley's model with Test~I cutting
   conditions to predict the basic cutting parameters that govern the physics of plastic
   deformation in metal cutting, so that the most important parameters that influence the
   level of AE could be evaluated. Besides, it was also concluded that the AE signals
   measured during Test~I (measured at the tool side) were manly generated due to plastic
   deformation at the tool-chip interface. Moreover, it was realized that $I_\mr{power}$
   is mostly influence by the effect of primary strain ($\gamma_\mr{AB}$), secondary
   strain rate ($\dot{\gamma}_\mr{int}$), and interface temperature $T_\mr{int}$. However,
   it was also found out that the effect of $T_\mr{int}$ on $I_\mr{power}$, if temperature
   $T_\mr{W}$ is kept constant, are masked by the influence of $\gamma_\mr{AB}$ and
   $\dot{\gamma}_\mr{int}$, and by using Test~I experimental results together with Oxley's
   model predictions, the following empirical relationship was established: $I_\mr{power}
   \propto \gamma_\mr{AB}^{n_1}\dot{\gamma}_\mr{int}^{n_2}$, where $n_1 = 4.5$ and $n_2 =
   2.4$. However, by analysing Test~IV results, where $T_\mr{W}$ was allowed to vary,
   $I_\mr{power}$ was clearly seen to decrease with $T_\mr{int}$, and the previous
   empirical relationship can not, therefore, be valid any longer.

   \item At the high strain rates and temperatures typically found in metal cutting,
   plastic deformation is governed by the motion of dislocation on the so-called viscous
   damping regime~\cite{kumar68,kumar69}. In this regime, the movement of dislocations is
   opposed by damping forces, which are proportional to dislocation speed, and also by the
   forces due to dislocation obstacles. Although theses two forces are responsible for the
   dynamics of the dislocations, and hence the dynamics of plastic deformation, it was
   suggested that only the forces posed by the obstacles could originate AE, since AE is
   composed by high frequency waves, and only the releases of strain energy due to the
   passage of dislocations over the obstacles could provide such high frequency emissions.
   According to the proposed model, the following trends were predicted: $I_\mr{power}$
   increases with strain and strain rate, but it decreases with temperature; and
   $f_\mr{mean}$ increases with strain rate, decreases with temperature, and it remains
   unaltered with strain. These trends were conformed by Test~I and~IV experimental data,
   indicating that the release of strain energy when a dislocations surmount obstacles may
   be the most relevant source of continuous AE during continuous chip generation
   processes.

\end{itemize}


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\section{Recommendations for Further Work} \label{sec:recommen}

In this section, in order to aid any future research work to be undertaken in the
areas covered by this thesis, some final recommendations and suggestions for possible
alterations are provided:
\begin{itemize}

   \item Since only prediction for the two carbon steel work materials were possible
   with Oxley's theory, an extension of the theory to use other type of work
   materials must be investigated. Some work has already been undertaken by
   Adibi-Sedeh~\etal~\cite{adibi-sedeh03} to extend Oxley's model for other type of
   steels, for aluminium alloys, and for copper. Moreover, it is also proposed that,
   once an extended Oxley's model has been accomplished, that metal cutting is
   simulated for the other two non-carbon steel work materials (stainless steel
   304S15 and aluminium alloy \mbox{6082-T6}), so that the basic cutting parameters,
   such as strain, strain rate, flow stress, and temperature can be predicted for
   these two materials as well. Subsequently, the relationship defined in
   Section~\ref{sec:energy_analysis} by Equation~\ref{eq:AE_S_AB_SR_int} should be
   verified for these other two work materials, since when tested for the two carbon
   steels, Equation~\ref{eq:AE_S_AB_SR_int} was observed to be material independent.
   All other analysis, such as the frequency analysis presented in
   Section~\ref{sec:frequency_analysis} and the temperature analysis presented in
   Section~\ref{sec:ae_temp}, should be repeated for the two work materials 304S15
   and \mbox{6082-T6}. Depending on the results of the analysis of these two
   non-carbon steel work materials, the qualitative model presented in
   Section~\ref{sec:disloc_AE} should be revalidated or modified accordingly.

   \item In order to obtain valuable results in Tests~II and~III, these tests should be
   repeated with longer acquisition lengths (more than 100~ms) of the AE data sets, so that
   the effect of unwanted busts can be removed from the computation of AE mode.

   \item If Test~I were to be repeated, the range of cutting conditions $V$ and $t_1$
   should be raised, since at low $V$ and $t_1$ values, the occurrence of built-up
   edge (BUE) was detected during the course of Test~I. When BUE is present, Oxley's
   model predictions do not agree so well with the experimental results
   (Figures~\ref{fig:[Oxley_R][speed]} and~\ref{fig:[Oxley_R][feed]}). Another reason
   to raise $V$ and $t_1$ is due to the fact that Oxley's model did not converge for
   some of the lowest vales of $V$ and $t_1$, and results for these conditions were
   found by extrapolation.

\end{itemize}
