Multi-criteria process optimization for better performance of grinding AISI 1060 hardened steel using different hybrid taguchi-based MCDM methods

Though the use of cutting oil is essential for a smooth machining process, it exposes some risks to the environment and the workers themselves. Unlike flood cooling, minimum quantity lubrication (MQL) ensures minimal application of fluid to do the job. Researchers are persistently trying to improve the performance of MQL techniques in various ways. One way is to introduce nanofluid in MQL. The excellent thermal conductivity and heat dissipation properties of nanofluid made it very popular in machining technology. Additionally, the use of compressed air during grinding can improve machining quality as it keeps the wheel surface free of loose grits and debris. The authors of the paper were especially intrigued by the prospect of examining the combined effects of MQL, nanofluid, and compressed air on the grinding process, as no previous study had thoroughly addressed each of these factors simultaneously. In this work, the grind ability of AISI 1060 high-speed steel has been investigated using four different machining environments which are dry condition, compressed air, pulse jet MQL, and compressed air with nanoparticles in MQL. The machining was performed on a Horizontal Spindle Surface Grinder with a CBN wheel in down-cut grinding mode. Performance parameters were four infeed rates (10, 20, 30 and 40 μm), two separate wheel speeds (1500 rpm and 3000 rpm), one fixed table speed rate of 6 m/min and one fixed MQL flow rate of 75 ml/h. Machining performance was measured in terms of cutting temperature and surface roughness. Entropy-based TOPSIS and VIKOR were used to optimize the machining parameters. Analysis reveals that compressed air with MQL demonstrates the best performance. At higher cutting speeds, the surface finish was better but the cutting temperature was also on the higher side. Different methods found different combinations of infeed and speed.