Research Information System
Multidiscipline Modeling in Materials and Structures, pp.1-21, 2025 (SCI-Expanded, Scopus)
Purpose – This study aims to investigate and optimize energy consumption during the bandsaw cutting of aluminium alloys commonly used in industry. By examining the influence of cutting speed, material type and tool wear on energy efficiency and tool performance, the research seeks to identify optimal process parameters that balance low energy use with extended tool life. The goal is to support more sustainable and cost-effective machining practices by reducing energy demand and associated carbon emissions while maintaining high cutting efficiency across different aluminium alloy series. Design/methodology/approach – Cutting experiments were conducted on 5000, 6000, and 7000 series aluminium alloys using a bandsaw under dry conditions at three cutting speeds (30, 60, and 90 m/min). Energy consumption was monitored via current index measurements, and specific energy and carbon footprint values were calculated. Tool wear and machinability were analysed using linear regression and Monte Carlo simulations. Response Surface Methodology (RSM) was applied to determine optimal cutting parameters for minimizing energy use while maximizing tool life. Findings – The 5000 series aluminium alloy demonstrated the lowest energy consumption and cutting force, making it the most energy-efficient option, though with shorter tool life. The 7000 series provided the longest tool life but required higher energy input. Optimal performance was achieved at a cutting speed of 60–70 m/min, balancing energy efficiency and tool durability. Specific Cutting Energy Coefficient (SCEC) and carbon footprint analyses confirmed that cutting parameters and material selection significantly affect sustainability. Monte Carlo and RSM analyses validated that process optimisation can reduce energy use by up to 27% and carbon emissions by 35%. Originality/value – This study uniquely integrates experimental data, statistical modelling (RSM) and Monte Carlo simulation to optimise energy consumption and tool performance during the bandsaw cutting of aluminium alloys. Unlike previous research, it introduces the Specific Carbon Footprint (SCF) metric to assess environmental impact alongside machinability. The work provides a comprehensive framework linking cutting parameters, alloy type, and sustainability outcomes. Its findings offer practical guidance for manufacturers aiming to enhance energy efficiency, reduce operational costs and minimise carbon emissions—contributing to more sustainable machining strategies in aluminium processing.