A new conventional criterion for the performance evaluation of gang saw machines

• Published in: Measurement
• Main Authors: Shaffiee Haghshenas, S., Shirani Faradonbeh, R., RezaMikaeil, R., Taheri, A., Saghatforoush, A., AlirezaDormishi, A.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Elsevier 2019
• Subjects: Gang saw machine; Carbonate rocks; Cutting dimension stones; Maximum electrical current; Gene expression programming; Multiple linear regression; sami
• Online Access: http://hdl.handle.net/2440/125723; https://doi.org/10.1016/j.measurement.2019.06.031

Available online 20 June 2019 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. Sina Shaffiee Haghshenas, Roohollah Shirani Faradonbeh, Reza Mikaeil, Sami Shaffiee Haghshenas, Abbas Taheri, Amir Saghatforoush, Alireza Dormishi