IEEE - Institute of Electrical and Electronics Engineers, Inc. - Optimizing Mining Track Equipment Undercarriage Shoe Life Using Convolution Neural Network

2018 IEEE 7th International Conference on Adaptive Science & Technology (ICAST)

Author(s): Harry Atta-Motte ; Eric Kuada ; Mark Amo-Boteng
Publisher: IEEE - Institute of Electrical and Electronics Engineers, Inc.
Publication Date: 1 August 2018
Conference Location: Accra, Ghana
Conference Date: 22 August 2018
Page(s): 1 - 8
ISBN (Electronic): 978-1-5386-4233-7
ISSN (Electronic): 2326-9448
DOI: 10.1109/ICASTECH.2018.8507140
Regular:

The health of track undercarriage equipment in the mining and construction industry requires a high degree of oversight in enhancing equipment availability and reliability to improve the usage... View More

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