Abstract: In this study, to clarify the effectiveness of an
aluminum/chromium/tungsten-based-coated tool for cutting sintered
steel, tool wear was experimentally investigated. The sintered steel
was turned with the (Al60,Cr25,W15)N-, (Al60,Cr25,W15)(C,N)- and
(Al64,Cr28,W8)(C,N)-coated cemented carbide tools according to the
physical vapor deposition (PVD) method. Moreover, the tool wear of
the aluminum/chromium/tungsten-based-coated item was compared
with that of the (Al,Cr)N coated tool. Furthermore, to clarify the tool
wear mechanism of the aluminum/chromium/tungsten-coating film for
cutting sintered steel, Scanning Electron Microscope observation and
Energy Dispersive x-ray Spectroscopy mapping analysis were
conducted on the abraded surface. The following results were
obtained: (1) The wear progress of the (Al64,Cr28,W8)(C,N)-coated
tool was the slowest among that of the five coated tools. (2) Adding
carbon (C) to the aluminum/chromium/tungsten-based-coating film
was effective for improving the wear-resistance. (3) The main wear
mechanism of the (Al60,Cr25,W15)N-, the (Al60,Cr25,W15)(C,N)-
and the (Al64,Cr28,W8)(C,N)-coating films was abrasive wear.
Abstract: Haynes 25 alloy (also known as L-605 alloy) is cobalt
based super alloy which has widely applications such as aerospace
industry, turbine and furnace parts, power generators and heat
exchangers and petroleum refining components due to its excellent
characteristics. However, the workability of this alloy is more
difficult compared to normal steels or even stainless. In present work,
an experimental investigation was performed under cryogenic
cooling to determine cutting tool wear patterns and obtain optimal
cutting parameters in turning of cobalt based superalloy Haynes 25.
In experiments, uncoated carbide tool was used and cutting speed (V)
and feed rate (f) were considered as test parameters. Tool wear
(VBmax) were measured for process performance indicators.
Analysis of variance (ANOVA) was performed to determine the
importance of machining parameters.
Abstract: In metal cutting industries, mathematical/statistical
models are typically used to predict tool replacement time. These
off-line methods usually result in less than optimum replacement
time thereby either wasting resources or causing quality problems.
The few online real-time methods proposed use indirect measurement
techniques and are prone to similar errors. Our idea is based on
identifying the optimal replacement time using an electronic nose to
detect the airborne compounds released when the tool wear reaches
to a chemical substrate doped into tool material during the
fabrication. The study investigates the feasibility of the idea, possible
doping materials and methods along with data stream mining
techniques for detection and monitoring different phases of tool
wear.