Abstract
In recent years, super duplex stainless steel (SDSS) has gained a lot of importance due to its strength and excellent resistance to corrosion cracking for applications in marine and chemical processing industries, etc. In spite of various progress in the field, the drilling of SDSS leads to the formation of chips that are very strong and abrasive, which makes it challenging to have proper drilling. To overcome this issue by utilizing suitable parameters such as drill bit coating, environmental conditions and parameters for drilling. The SDSS machining output results were compared for both dry and minimum quantity lubrication (MQL) conditions using coated and uncoated drill bits. A scalable pulse power plasma (S3P) technique was utilized to deposit the titanium silicon nitride (TiSiN) and aluminum titanium nitride (AlTiN) coatings on solid carbide drill bits. In the experiments, three levels of drilling parameters have been chosen, including spindle speed (550, 700, 850 rpm), feed rate (0.035, 0.045, 0.060 m/min), and drill bit types. The experiment was designed using Taguchi's orthogonal L9 array. The influence of machining parameters such as cutting force, surface roughness, and circularity error were examined using variance analysis (ANOVA) and signal-to-noise (S/N) ratios. To enhance the drilling process parameters through a single comprehensive output measure, the obtained results were taken as an input to the fuzzy logic networks using multi-factor analysis. At the L7 trial, the least cutting force was observed at 525.7 N for dry conditions and 227.6 N for MQL conditions and gave cone-spiral and continuous chips. In order to analyze the signal-to-noise ratio effectively, high value correspond to better-quality characteristics. In accordance with ANOVA results pertaining to cutting force, a percentage contribution variance of 48.92% was obtained for the feed rate, which contributed to cutting force to a greater extent, followed by 36.82% for spindle speed and 14.19% for the type of drill bit.
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