Sustainable drilling performance optimization for Nano SiC reinforced Al matrix composites

Metal Matrix Composites (MMC) reinforced by nanoparticles are competent materials, appropriate for functional and structural applications. Green manufacturing is a style for mechanized that minimizes dissipate and contamination. The pollution prevention resolves in manufacturing industries to expand and execute various environmentally-friendly strategies. The primary purpose of green machining is to hold up future generations by attaining process sustainability. In the present investigation, cryogenic machining (CM) of Nanoscaled SiC reinforced Aluminum (Al) matrix composites gives experimental outcomes and also the correlation of its performance with dry machining (DM) and Minimum Quantity Lubrication (MQL). The drilling tests are organized using a vertical machining center (VMC), which is directed by computer numeric control (CNC) employing carbide drills of 10 mm dia with cutting point angles of 90, 118, and 135 degrees. Experiments have planned as per the response surface methodology (RSM) based on Box-Behnken design (BBD). Teaching-Learning-Based Optimization (TLBO) is implemented to optimize the drilling criteria such as the speed of the spindle, feed rate, weight % of nano SiC, and cutting angle. Subsequently, Scanning Electron Microscope (SEM) is utilized to inspect the subsurface of the machined specimen.