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Type: Journal article
Title: A new conventional criterion for the performance evaluation of gang saw machines
Author: Shaffiee Haghshenas, S.
Shirani Faradonbeh, R.
RezaMikaeil, R.
Shaffiee Haghshenas, S.
Taheri, A.
Saghatforoush, A.
AlirezaDormishi, A.
Citation: Measurement, 2019; 146:159-170
Publisher: Elsevier
Issue Date: 2019
ISSN: 0263-2241
Statement of
Sina Shaffiee Haghshenas, Roohollah Shirani Faradonbeh, Reza Mikaeil, Sami Shaffiee Haghshenas, Abbas Taheri, Amir Saghatforoush, Alireza Dormishi
Abstract: The process of cutting dimension stones by gang saw machines plays a vital role in the productivity and efficiency of quarries and stone cutting factories. The maximum electrical current (MEC) is a key variable for assessing this process. This paper proposes two new models based on multiple linear regression (MLP) and a robust non-linear algorithm of gene expression programming (GEP) to predict MEC. To do so, the parameters of Mohs hardness (Mh), uniaxial compressive strength (UCS), Schimazek’s F-abrasiveness factor (SF-a), Young’s modulus (YM) and production rate (Pr) were measured as input parameters using laboratory tests. A statistical comparison was made between the developed models and a previous study. The GEP-based model was found to be a reliable and robust modelling approach for predicting MEC. Finally, according to the conducted parametric analysis, Mh was identified as the most influential parameter on MEC prediction.
Keywords: Gang saw machine; Carbonate rocks; Cutting dimension stones; Maximum electrical current; Gene expression programming; Multiple linear regression
Description: Available online 20 June 2019
Rights: © 2019 Elsevier Ltd. All rights reserved.
DOI: 10.1016/j.measurement.2019.06.031
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Appears in Collections:Aurora harvest 4
Civil and Environmental Engineering publications

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