Reza Mikaeil - Department of Mining and Engineering, Faculty of Environment, Urmia University of Technology, Urmia, Iran.
Akbar Esmaeilzade - Department of Mining and Engineering, Faculty of Environment, Urmia University of Technology, Urmia, Iran.
Sina Shaffiee Haghshenas - Department of Civil Engineering, University of Calabria, ۸۷۰۳۶ Rende, Italy.

Predicting the current consumption of cutting machines in cutting building stones can be one of the most fundamental steps to achieve optimal conditions from energy consumption in the building stone cutting industry. Therefore, it is necessary to study the relationship between the operational characteristics of the machine and the work piece with the amount of consumed energy by the machine. In this paper, an attempt has been made to provide a precise model for predicting the current consumption of cutting machines using statistical studies. For this purpose, laboratory studies were performed under different operational conditions such as different depths of cut (۱۵, ۲۲, ۳۰, and ۳۵ mm) and different feed rates (۱۰۰, ۲۰۰, ۳۰۰, and ۴۰۰ cm/min). During the sawing process, ۱۲ samples of soft and hard rock were studied by using a cutting machine on a laboratory scale (with the ability to change machining parameters and equipped with measuring current consumption). Following laboratory studies, rock samples were transferred to the rock mechanics laboratory to determine Schimazek's F-abrasiveness factor. After determining the abrasion of the samples, statistical studies were performed by using the SPSS software. Thus, the new statistical models were presented to predict the current consumption of the cutting machine based on the abrasion of the building stone sample, cutting depth, and the progress rate of the workpiece as an independent variable. The proposed statistical models can be used with high reliability to estimate the current consumption in the cutting process.

Current consumption, Machine parameters, Schimazek's F-abrasiveness factor, Statistical models