Abstract: Noteworthy results have been obtained in the turning and drilling of hardened high-strength steels using tungsten carbide based cutting tools. In a finish turning process, it was seen that surface roughness and tool flank wear followed very different trends against cutting time. The suggested explanation for this behaviour is that the profile cut into the workpiece surface is determined by the tool’s cutting edge profile. It is shown that the profile appearing on the cut surface changes rapidly over time, so the profile of the tool cutting edge should also be changing rapidly. Workpiece material adhered onto the cutting tool, which is also known as a built-up edge, is a phenomenon which could explain the observations made. In terms of tool damage modes, workpiece material adhesion is believed to have contributed to tool wear in examples provided from finish turning, thread turning and drilling. Additionally, evidence of tool fracture and tool abrasion were recorded.
Abstract: Machining of hard materials is a recent technology for
direct production of work-pieces. The primary challenge in
machining these materials is selection of cutting tool inserts which
facilitates an extended tool life and high-precision machining of the
component. These materials are widely for making precision parts for
the aerospace industry. Nickel-based alloys are typically used in
extreme environment applications where a combination of strength,
corrosion resistance and oxidation resistance material characteristics
are required. The present paper reports the theoretical and
experimental investigations carried out to understand the influence of
machining parameters on the response parameters. Considering the
basic machining parameters (speed, feed and depth of cut) a study has
been conducted to observe their influence on material removal rate,
surface roughness, cutting forces and corresponding tool wear.
Experiments are designed and conducted with the help of Central
Composite Rotatable Design technique. The results reveals that for a
given range of process parameters, material removal rate is favorable
for higher depths of cut and low feed rate for cutting forces. Low feed
rates and high values of rotational speeds are suitable for better finish
and higher tool life.
Abstract: The wear of cutting tool degrades the quality of the product in the manufacturing processes. The on line monitoring of the cutting tool wear level is very necessary to prevent the deterioration of the quality of machining. Unfortunately there is not a direct manner to measure the cutting tool wear on line. Consequently we must adopt an indirect method where wear will be estimated from the measurement of one or more physical parameters appearing during the machining process such as the cutting force, the vibrations, or the acoustic emission etc…. In this work, a neural network system is elaborated in order to estimate the flank wear from the cutting force measurement and the cutting conditions.
Abstract: This study presents a new method for detecting the
cutting tool wear based on the measured cutting force signals using
the regression model and I-kaz method. The detection of tool wear
was done automatically using the in-house developed regression
model and 3D graphic presentation of I-kaz 3D coefficient during
machining process. The machining tests were carried out on a CNC
turning machine Colchester Master Tornado T4 in dry cutting
condition, and Kistler 9255B dynamometer was used to measure the
cutting force signals, which then stored and displayed in the DasyLab
software. The progression of the cutting tool flank wear land (VB)
was indicated by the amount of the cutting force generated. Later, the
I-kaz was used to analyze all the cutting force signals from beginning
of the cut until the rejection stage of the cutting tool. Results of the IKaz
analysis were represented by various characteristic of I-kaz 3D
coefficient and 3D graphic presentation. The I-kaz 3D coefficient
number decreases when the tool wear increases. This method can be
used for real time tool wear monitoring.
Abstract: An attempt has been made to investigate the
machinability of zirconia toughened alumina (ZTA) inserts while
turning AISI 4340 steel. The insert was prepared by powder
metallurgy process route and the machining experiments were
performed based on Response Surface Methodology (RSM) design
called Central Composite Design (CCD). The mathematical model of
flank wear, cutting force and surface roughness have been developed
using second order regression analysis. The adequacy of model has
been carried out based on Analysis of variance (ANOVA) techniques.
It can be concluded that cutting speed and feed rate are the two most
influential factor for flank wear and cutting force prediction. For
surface roughness determination, the cutting speed & depth of cut
both have significant contribution. Key parameters effect on each
response has also been presented in graphical contours for choosing
the operating parameter preciously. 83% desirability level has been
achieved using this optimized condition.
Abstract: Monitoring the tool flank wear without affecting the
throughput is considered as the prudent method in production
technology. The examination has to be done without affecting the
machining process. In this paper we proposed a novel work that is
used to determine tool flank wear by observing the sound signals
emitted during the turning process. The work-piece material we used
here is steel and aluminum and the cutting insert was carbide
material. Two different cutting speeds were used in this work. The
feed rate and the cutting depth were constant whereas the flank wear
was a variable. The emitted sound signal of a fresh tool (0 mm flank
wear) a slightly worn tool (0.2 -0.25 mm flank wear) and a severely
worn tool (0.4mm and above flank wear) during turning process were
recorded separately using a high sensitive microphone. Analysis
using Singular Value Decomposition was done on these sound
signals to extract the feature sound components. Observation of the
results showed that an increase in tool flank wear correlates with an
increase in the values of SVD features produced out of the sound
signals for both the materials. Hence it can be concluded that wear
monitoring of tool flank during turning process using SVD features
with the Fuzzy C means classification on the emitted sound signal is
a potential and relatively simple method.