Improvement of manufacturing productivity is dependent on the successful
automation of manufacturing processes, the success of which is based in turn upon
the availability of information which describes the state of manufacturing operations.
Acoustic Emission (AE) signals related to the cutting process and tool wear have
been recently applied to monitor manufacturing processes, and various AE parameters
can be used to provide process information. For example, when cutting tools
become worn, AE energy generated at the interface of tool flank and work piece
increases. This study is thus an experimental investigation of the AE spectrums representing
AE signals energy distribution to determine the possibility of extracting
useful parameters to provide on-line information about drilled-hole quality and drill-bit
wear.
An experiment conducted using a radial-arm drilling machine was employed
to collect on-line AE drilling process spectrums, yielding eight indicator parameters.
Drill wear states were measured using a machine vision system. Assessment of the
drilled hole quality was based on tolerances established in Geometric Dimensioning and Tolerancing (GD&T). Correlations among drill wear, drilled-hole quality measurements,
and the AE spectrum indicator parameters were examined by regression
analysis. A forward-stepwise variable selection procedure was used to select the
best-fit regression model for each drilled hole quality measurement associated with
the set of one AE parameter raised to different powers. According to quality measurements,
drilled holes were categorized as either "acceptable" or "unacceptable"
holes, using cluster analysis with a group-averaging method. The usage of AE
parameters to decide to which group a drilled hole belonged was also examined.
From the experimental evidence, it was observed that there are strong
relationships between AE parameters and drill-wear state and the quality measurements
of drilled holes. AE parameters could be useful predictor variables to provide
information to controller/operators to evaluate current drilling processes. Based on
the status information of drill wear and the quality measurements, drilling processes
can be adjusted accordingly. / Graduation date: 1997
| Identifer | oai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/34003 |
| Date | 30 August 1996 |
| Creators | Wang, Kuang-Jen, 1962- |
| Contributors | Paasch, Robert K. |
| Source Sets | Oregon State University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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