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Abstract
The implementation of magnesium alloys in a multitude of industries has been proven to be a mere effect of their attractive light weight, corrosion resistant, and biodegradable properties. These traits allow these materials to portray an excellent sustainable machinability. However, with increasing demand, it is essential to explore sustainable means of increasing production while mitigating reductions in sustainability. The current work aims to assess and optimize the high-speed machinability of AZ91 with the use of a vegetable oil-based minimum quantity lubrication (MQL) system using the grey relational analysis (GRA) on the basis of chip morphology and tool wear. The investigation entailed a full factorial design with MQL flow rate, cutting speed, and feed rate as the control parameters and flank wear, land width, chip contact length, saw-tooth pitch, chip segmentation ratio, chip compression ratio, and shear angle as the output responses. The optimal control parameters predicted and experimentally confirmed were an MQL flow rate of 40 mL/h, cutting speed of 300 m/min, and feed rate of 0.3 mm/rev. The usage of said optimal parameters results in a grey relational grade improvement of 0.2675 in comparison to the referenced first experimental run. Moreover, the MQL flow rate was regarded as the critical variable with a contribution percentage of 20% for the grey relational grade.
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