Assessing the System Vibration of Circular Sawing Machine in Carbonate Rock Sawing Process Using Experimental Study and Machine Learning

Abstract Predicting the vibration of circular sawing machine is very important in examining performance process, as it shows amount energy consumption machine. Also, this factor directly related to maintenance cost, such that with a small increase level vibration, cost increases large extent. This paper presents new prediction models assess An evaluation model based on imperialist competitive algorithm one most efficient artificial intelligence techniques was used for estimation sawability dimension stone carbonate rocks. For purpose, four main physical and mechanical properties rock including Schimazek’s F-abrasivity, uniaxial compressive strength, mean Mohs hardness, Young’s modulus well two operational parameters depth cut feed rate, were investigated measured. In predicted model, system considered dependent variable. The results showed can be using newly developed learning models. It suitable properties.