Abstract
The high demand of Ti-6Al-4V in medical industries becoming a concern nowadays.
Titanium is a suitable material for orthopedic implants, dentistry and cardiovascular
aids due to high resistance, immunity to corrosion, high fracture strength,
osseointegration, low modulus and density. As the titanium is one of the most expensive
materials and is categorised as a difficult-to-machine material, it is governed by the
limitation of being machined through conventional machining. Hence, the problem in
machining titanium can be solved by an alternative non-conventional machining
process. A wire electro-discharge machining (WEDM) is able to machine the
electrically conductive materials and with no physical contact between the workpiece
and wire electrode which aids in keeping the material non-toxic for medical
applications. The toxicity of the material has to be tested by way of biocompatibility
testing. This research aims to develop the machining WEDM surface roughness
prediction model through Artificial Neural Network (ANN), to characterise the
machined surface of Ti-6Al-4V through WEDM and to determine the influences of
machining processes on the biocompatibility of the machined part. The preliminary
WEDM cutting operation helps in identifying the parameters and levels for the actual
WEDM process. There are five phases in investigating the WEDM process of Ti-6Al-
4V. Phase I is preliminary WEDM cutting operation, Phase II is mathematical
prediction modelling on surface roughness by ANN, Phase III is sample preparation,
Phase IV is machined surface observation and Phase V is cytotoxicity testing. In this
study, three parameters which are pulse-off time, peak current and wire tension applied
to WEDM process to achieve desired output performance. The experimental surface
roughness is compared with predicted surface roughness using the Artificial Neural
Network to optimise combination of parameters. It is found that, the lowest surface
roughness (1.3770 μm) with minimum error percentage 0.5434 % obtained by the best
combined parameters; 2 μs pulse-off time, 12 N wire tension and 10 A peak current.
The pulse-off time is less significant on surface roughness observation. The effect of
the machining process that is observed are the surface roughness, surface topography,
elementary analysis and microhardness. The thickness of the white layer depends on the
discharge energies at the gap between the wire electrode and the workpiece. The
elements of Ti-6Al-4V maintained after the machining process. There are existence of
zinc, carbon and oxygen that migrates from the workpiece and deionized water. The
microhardness increased below the surface as the machined surface experiences thermal
softening due to high temperatures. The biocompatibility of Ti-6Al-4V with L929 cells
is based on the cell culture and cell viability testing showed 80% positive cell viability
for each concentration of Ti-6Al-4V medium.
Metadata
Item Type: | Thesis (Masters) |
---|---|
Creators: | Creators Email / ID Num. Musa, Nornisaadila 2017864522 |
Contributors: | Contribution Name Email / ID Num. Thesis advisor Saedon, Juri (Dr.) UNSPECIFIED |
Subjects: | Q Science > QC Physics > Atomic physics. Constitution and properties of matter |
Divisions: | Universiti Teknologi MARA, Shah Alam > Faculty of Mechanical Engineering |
Programme: | Master of Science (Mechanical Engineering) |
Keywords: | Electro-discharge machining (WEDM); titanium alloy; artificial intelligence; surface observation; biocompatibility |
Date: | May 2020 |
URI: | https://ir.uitm.edu.my/id/eprint/54136 |
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