Showing 2 results for Ghazi khansari
Vahid Tahmasbi , Amin Sousanabadi Farahani , Baghi , Ghazi khansari ,
Volume 23, Issue 10 (October 2023)
Abstract
Metal composites have received attention from various industries due to their excellent properties, such as a high strength-to-weight ratio and wear resistance. However, due to the presence of hard and abrasive particles, the challenges have always faced machining. Therefore, studying the effective parameters in the machining of these materials is very important. Drilling is one of the most common and widely used methods in the industry. In this study, the Response Surface Method (RSM) and Central Composite Design (CCD) were used to model, optimize, and analyze the effects of machining parameters. Aluminum composite with AL356 alloy reinforced with 25 micrometers of silicon carbide and 45 micrometers of mica mineral, as well as a 6 mm diameter carbide drill, were used for the experiments. According to the results, with an increase in the drilling speed, the drilling forces increased and the surface roughness decreased. Additionally, increasing the feed rate increased forces and surface roughness. With an increase in the volume fraction of SiC reinforcing particles, the drilling forces and surface roughness increased and decreased, respectively. By analyzing the data obtained from the experiments, the best combination of values was found to minimize the surface roughness and axial force at the same time. The best combination of parameters was found to be: a spindle speed of 1855 rpm, a feed rate of 50 mm/rev, and a weight percentage of 15% SiC
Vahid Tahmasbi , Amin Sousanabadi Farahani , Danial Ghazi khansari , Mohammad Hafez Baghi ,
Volume 23, Issue 10 (October 2023)
Abstract
Due to the significant increase in demand for materials with new capabilities, the use of composite materials is increasing. These materials have unique properties such as high wear resistance and a high strength-to-weight ratio, and are used by engineers in various industries, particularly in the aerospace and automotive sectors. Due to the metallic nature of these materials, the machining process is an integral part in achieving the shape and properties of the final product. Among composite materials, aluminum-based composites are the most widely used in industry. In this study, a methodical was conducted, study including statistical modeling using the response surface method and deriving regression equations of the effect of spindle rotation speed, feed rate, and depth of cut on surface roughness, metal removal rate, and tool wear during machining of A359/B4C/Al2O3 matrix aluminum composite. It was found that an increase in spindle rotation speed, feed rate, and cutting depth increased metal removal. The best combination of parameters that was found to simultaneously minimize the surface roughness and maximize the metal removal rate and minimize flank wear was a spindle speed of 600 rpm, a feed rate of 0.075 mm/rev, and a cutting depth of 0.20 mm
