An insight on optimization of FSP process parameters for the preparation of AA5083/(SiC-Gr) hybrid surface composites using the response surface methodology

Abstract

Aluminum alloys are known for their extensive use in aerospace, automobile, marine, etc., industries due to their excellent inherent properties. Recent studies have developed different methods to modify the surface properties of aluminum by producing surface composites, such as the friction stir processing (FSP) method. The current study made an effort to develop a new hybrid surface composite of AA5083/(SiC-Gr) using the FSP method. For FSP process optimization, the response surface methodology (RSM) has been used. For creating the mathematical model using RSM, various input process parameters of the FSP are selected to predict the output characteristics of the prepared hybrid composite. A Box–Behnken design was used for the process with four factors, each factor was used with three levels, and the RSM was utilized to form a regression model to predict the responses. The ANOVA analysis suggests that NoP (number of passes): 3 and RV (reinforcement volume): 75:25 (SiC: Gr) ratio are the significant parameters of the study with a p-value less than .05. The novelty of this study lies in the development of a new hybrid surface composite of AA5083/(SiC-Gr) using the friction stir processing (FSP) method, with optimization achieved through the response surface methodology (RSM) and multi-objective selection criteria, resulting in predicted outcomes within a range of ±10% of the experimental observations.