Modeling and optimization of cutting forces and effect of turning parameters on SiCp/Al 45% vs SiCp/Al 50% metal matrix composites: a comparative study

Abstract

In this study, the proposed experimental and second-order model for the cutting forces were developed through several parameters, including cutting speed, feed rate, depth of cut, and two varying content of SiCp. Cutting force model was developed and optimized through RSM and compared for two different percentages of components SiCp/Al 45% and SiCp/Al 50%. ANOVA is used for Quantitative evaluation, the main effects plot along with the evaluation using different graphs and plots including residual analysis, contour plots, and desirability functions for cutting forces optimization. It provides the finding for choosing proper parameters for the machining process. The plots show that during increment with depth of cut in proportion with feed rate are able to cause increments in cutting forces. Higher cutting speed shows a positive response in both the weight percentage of SiCp by reducing the cutting force because of higher cutting speed increases. A very fractional increasing trend of cutting force was observed with increasing SiCp weight percentages. Both of the methods such as experiment and model-predicted results of SiCp/Al MMC materials were thoroughly evaluated for analyzing cutting forces of SiCp/Al 45%, and SiCp/Al 50%, as well as calculated the error percentages also found in an acceptable range with minimal error percentages. Article Highlights This study focuses on the effect of cutting parameters as well as different percentage of SiC particles on the cutting forces, while comparing the results of both SiC particles such as SiCp/Al 45%, and SiCp/Al 50% the result shows that there isn’t fractional amount of impact on the cutting force with nominal increasing percentages of SiC particles. Cutting speed in machining process of SiCp/Al shows positive response in reducing the cutting forces, however, increasing amount of depth of cut followed by increasing feed rate creates fluctuations in cutting force and thus increases the cutting force in the cutting process. The developed RSM mathematical model which is based on the box Behnken design show excellent competence for predicting and suggesting the machining parameters for both SiCp/Al 45%, and SiCp/Al 50% and the RSM mathematical model is feasible for optimization of the machining process with good agreement to experimental values.

A Review on Machining SiCp/Al Composite Materials

“…Tool wear predominantly occurs on the flank surface, necessitating the prediction of tool wear. Researchers such as Saeed [ 48 ] and Rashid et al [ 49 , 50 ] have employed turning experimental devices and artificial neural networks (ANNs) to predict the lateral wear of the tool. They analyzed the influence of process parameters on tool surface wear.…”

Multi-Response Optimization of Drilling Parameters for Aluminum Metal Matrix Composite Using Entropy Weighted Grey Relational Analysis

“…The optimal value of the input parameters given by RSM is 1000 rpm, feed 0.15 mm/rev, and depth of cut 0.3 mm for all three composites. Laghari et al [17] optimized the turning of a composite reinforced with SiC particles. They have found that the percentage of SiC reinforcement has no major effect on the cutting forces; on the other hand, the cutting force is more influenced by the cutting parameters, i.e.…”

Analyze the Effect of Crater Cutting Tool Wear Modeling in the Machining of Aluminium Composite

“…Response surface methodology investigates the interaction between several descriptive variables and response variables. The optimal factor and their effect was attained in turning process of aluminium composite using RSM 25 . Quadratic model and optimization was used to evaluate the cutting forces in turning of SiC based Al composite 26 .…”