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Title: Acquisition of Real-Time Operation Analytics for an Automated Serial Sectioning System

Journal Article · · Integrating Materials and Manufacturing Innovation

Mechanical serial sectioning is a highly repetitive technique employed in metallography for the rendering of 3D reconstructions of microstructure. While alternate techniques such as ultrasonic detection, micro-computed tomography, and focused ion beam milling have progressed much in recent years, few alternatives provide equivalent opportunities for comparatively high resolutions over significantly sized cross-sectional areas and volumes. To that end, the introduction of automated serial sectioning systems has greatly heightened repeatability and increased data collection rates while diminishing opportunity for mishandling and other user-introduced errors. Unfortunately, even among current, state-of-the-art automated serial sectioning systems, challenges in data collection have not been fully eradicated. Therefore, this paper highlights two specific advances to assist in this area; a non-contact laser triangulation method for assessment of material removal rates and a newly developed graphical user interface providing real-time monitoring of experimental progress. Furthermore, both are shown to be helpful in the rapid identification of anomalies and interruptions, while also providing comparable and less error-prone measures of removal rate over the course of these long-term, challenging, and innately destructive characterization experiments.

Research Organization:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
AC04-94AL85000
OSTI ID:
1333618
Report Number(s):
SAND-2016-8182J; 646817
Journal Information:
Integrating Materials and Manufacturing Innovation, Vol. 6, Issue 2; ISSN 2193-9764
Publisher:
SpringerCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 5 works
Citation information provided by
Web of Science

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Cited By (1)

Progress toward autonomous experimental systems for alloy development journal April 2019