MULTI-OBJECTIVE OPTIMIZATION OF ENERGY CONSUMPTION AND SURFACE ROUGHNESS IN 5-AXIS CNC MACHINING USING THE NSGA-II METHOD

• Main Author: Yahya, Najmuddin
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/84711
• Institution: Institut Teknologi Bandung

Optimization in CNC machining processes is essential for enhancing performance and efficiency. Energy consumption during the cutting process is a key optimization target, as researchers and manufacturers aim to achieve minimal energy use in CNC machining to reduce operational costs. On the other hand, consumers demand high product quality, and one measure of this quality is surface roughness, with lower values indicating better quality. The use of coolant in the cutting process can reduce surface roughness, but it also increases energy consumption due to the pump required to circulate the coolant. This study addresses the challenge of minimizing energy consumption while simultaneously minimizing surface roughness in products cut using a Hartford 5A-25R 5-Axis CNC machine. Five parameters, each with three levels—spindle speed, feed rate, depth of cut, width of cut, and coolant mode—were investigated. A Taguchi Orthogonal array L27 Design of Experiment was employed to derive regression equations for the multi- objective optimization process using the Non-dominated Sorting Genetic Algorithm II (NSGA-II). The NSGA-II process yielded a Pareto optimal front, representing optimal values for both objectives without dominance, indicating a trade-off between energy consumption and surface roughness. Experimental verification of the optimal front solutions showed errors below 10% for each objective, which is within acceptable limits.