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 RESEARCH AT
LOUGHBOROUGH UNIVERSITY
I have been involved with
monitoring systems for a while by now
and has become specialised in this
field. My interest in monitoring systems
started with a process surveillance
system, which I developed in Denmark for
the company Bang & Olufsen. The system was mainly an up/down time
monitoring system which was able to log the run and no run conditions of
their production equipment. The data from this was treated statistically
and the program was able to give a clear image of where problems arises,
regarding the production capacity. As a mechanical Engineer with an industrial
background, I have an interest in optimizing production equipment. I
have an M.Sc. in Mechatronics from Loughborough University UK,
where my major was Condition Monitoring of CNC Machinery. During my Ph.D, also at Loughborough University
connected to Holywell Mechatronic Research Centre, I have been occupied
with the field of Condition Monitoring Of Tools in CNC Machines. This is
the discipline of monitoring cutting tools in primarily metal cutting
machines, such as lathes and milling machines, to detect early signs of
wear and fracture. It is my opinion that modern companies should focus
on optimizing and automate the monitoring processes of their production
equipment, in order to get a economic and efficient control.
Machine monitoring is an efficient tool of actually telling the company
where to apply resources and where in the production problems arises.
AUTOMATED PRODUCTIONS
SHOULD HAVE AUTOMATED MONITORING SYSTEMS
There can be many reasons why
companies want to invest in monitoring systems, but one common objective
is of course the financial aspect, of being able to reduce either
downtime or faulty items due to poor quality. Due to an increased
automation the needs for monitoring systems should also be increased.
When the manual labour is moved away from the production the production
becomes unattended and hence, the risk of catastrophic breakdowns is
increased.
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CONDITION MONITORING OF CUTTING TOOLS
Tool Condition
Monitoring is the discipline
of monitoring cutting
tools for wear signs and
fracture. This monitoring
discipline is very
interesting, especially from
an industrial point of view.
Every year companies are
using massive resources due
to the consequences of tool
wear and fracture.
"An Electronic Copy of The
Human Ear".
The
TCM system is basically, what
could be said to be an
electronic copy of the human
ear and mechanism for
recognising sound.
Airborne Acoustic Emission (sound)
emitted from the machining
process is monitored in the
sonic range up to 20 kHz.
Humans are very good at
capturing signals, separate
these and recognise patterns,
so why not automate this ?
It is commonly know that skilled and trained operators are capable of
hearing changes in the tool condition. These changes can be recognised
in the frequency domain up to 20 kHz, for a human being with a normal
hearing. The difficult part of this research is to separate
and recognise the sound signals, because this must be done with a narrow
error margin to eliminate false predictions. Researchers in this field has normally been using the
frequency domain of recognising wear but as a novelty approach I am
linking the sound to tool wear through the use of surface finish. This way of monitoring will not only give an
estimation of progressed tool wear and upcoming failures, but could also
serve as an indicator for quality inspection.
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