Abstract
This thesis presents research and evaluation of the various phenomena that
potentially contain worthwhile information in the performance of machining
operations. In particular what these phenomena can tell a computer-controlled
machine, or the machine operator, about the degree of tool wear being
experienced during the operation. Tool wear is an unavoidable element of
machining operations and a variety of approaches have been investigated and
implemented to delay the onset of wear, e.g. cutting fluid, tool coatings.
However, there is currently no reliable system whereby tool wear itself can be
monitored during the cutting operation; this information is only available at the
end of the operation, through tool or work piece inspection and interrogation.
It was the intention of this research to determine which of the machining
phenomena, or fusions of these phenomena, is likely to provide the most
worthwhile information for such monitoring. All the data gathered during this
research and presented in this thesis was from machines working in a
commercial environment, carrying out typical live production cutting operations,
thus providing data that could be worthwhile for modern industry.
While this work started as the author’s own research into process monitoring of
the machining process, it expanded into an FP7 funded project with the
acronym “REALISM” Realism project (2015), with the author’s organisation
Schivo and WIT as the Lead Partners. This pan-European project formally
commenced in Jan 2014 and had a 2-year duration, concluding at the end of
2015. REALISM’s aim was to build and test a tool condition monitoring system
and, based on that, to lay the groundwork for the future goal of optimizing tool
usage and the tool change decision.
Original language | English |
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Awarding Institution | |
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Publication status | Unpublished - 2018 |
Keywords
- Tool condition performance monitoring