Optimising subsurface integrity and surface quality in mild steel turning: A multi-objective approach to tool wear and machining parameters

This study investigates the impact of machining parameters and tool dynamics on mild steel degradation of surface quality and subsurface, including heat effects, deformation, and microstructural changes that lead to microcracks and work hardening. Firstly, we examined the individual impacts of cutting velocity (Vc), feeding rate (f), and depth of cut (ap) on surface roughness and surface topography. Secondly, an examination was conducted to assess the influence of tool wear on the morphology of the turning surface using the white light interferometer (ZYGO). Finally, this study employs Grey Relational Analysis (GRA), Data Environment Analysis Ranking (DEAR), and Multi-objective Optimization based on Ratio Analysis Method (MOORA) optimization techniques with S/N ratios to refine 3D surface roughness (Sa, Sz, Sq) and material removal rates (MRR) in mild steel turning using a CVD-coated carbide tool. Key findings reveal that increasing Vc reduces surface roughness and improves morphology, while higher f and ap deteriorate both. Tool wear progresses through three stages, with the poorest surface quality occurring in the final stage. The results showed that cutting speed is the most influencing parameter on surface roughness in wet (43.37%) and dry (56.66%) turning, followed by feed rate (wet: 6.90%, dry: 7.71%) and depth of cut having minimal impact (wet: 2.04%, dry: 0.12%). The optimal machining parameters, determined as Vc = 125.6 m/min, f = 0.35 mm/rev, and ap = 0.7 mm, demonstrate the efficacy of the optimization techniques in achieving enhanced surface quality and making a significant contribution to the field of machining and manufacturing.