Abstract:
The unique physical features and reliability of advanced composite materials have attracted interest in recent years. Aluminum MMCs reinforced with SiC particles (Al/SiC-MMC) exhibit a yield strength increase of up to 20%, a greater modulus of elasticity, a lower coefficient of thermal expansion, and are more resistant to wear than the corresponding unreinforced matrix alloy systems. Despite having many benifits, Al/SiC-MMC shows poor machinability. Process such as grinding is crucial for the material to obtain aquality finish and damage-free surfaces. But soft aluminum alloys have poor grindability due to chip adherence, thereby clogging the wheel. Periodic dressing is required to avoid the aforementioned issues, which makes the grinding process inefficient. An effective cooling approach thus needs to be used with optimal process parameters that will enhance the grindability of the Al/SiC-MMC. The present work investigates the effects of the application of ecofriendly ZnO-deionized water nanofluid on the grindability of Al/SiC-MMC by CBN grinding wheel in respect of chip morphology, grinding temperature, surface roughness, wheel wear, and grinding ratio. A suitable MQL set-up has been designed and fabricated to deliver variable MQL flow rate continuously at the critical zones during surface grinding of the workpiece. In order to prepare the nanofluids, 0.5% volume of ZnO & Sodium dodecyl sulphate (SDS) surfactant are dispersed in the deionized water performing ultra-sonication & magnetic stirring for thirty minutes each. Experiments are designed using central composite design and empirical models are developed to predict grinding temperature, wheel wear, and surface roughness through RSM for flood cooling & MQL. Based on the experimental data, empirical model for predicting surface roughness has been developed using artificial neural network. Application of the produced nanofluids through MQL significantly reduces the cutting temperature, surface roughness, & wheel wear of the material and improves the grinding ratio compared to conventional flood cooling method. Significant reduction inclogging of the workpiece material into the CBN grinding wheel is observed for the MQL compared to dry grinding and flood cooling. Spindle speed 3000 rpm, infeed 10 µm, and environment nMQL have been selected using RSM based composite desirability approach to be the desired optimal combination for enhancing the grindability of Al/SiC-MMC.
