Improvement of energy efficiency using a multi-input fuzzy logic controller in a stone cutting machine

Abstract

Block cutter machines (BCMs) are commonly used in the manufacturing of natural stones. Although the energy consumption of the BCM is affected by the rotation speed of the blade, depth of cut, and traverse speed, these parameters are generally fixed. Unfortunately, stones are not homogeneous materials, and this has a negative impact on the energy consumption of the BCM because of the fixed parameters. The main goal of our study was the development of a multi input single output (MISO) fuzzy logic controller (FLC) design to improve the energy efficiency of the BCM. In this study, two MISO FLCs (two- and three-input) were designed to adjust the traverse speed and these controllers were applied in the laboratory-scale model of the BCM. The designed FLCs are tested with cutting experiments on three different stones. The experiments showed that, with the continuous adjustment of the traverse speed during the cutting process, the FLCs increase energy efficiency. The three-input FLC provided more energy saving than with the two-input FLC. Also, multiple regression analysis was performed in order to determine the combined effects of the most dominant rock properties on specific energy for three different control methods.