Optimization of cutter geometrical features and machining parameters for Machining Aluminium Silicon Carbide (AlSiC) using RSM

• Main Author: Rosman, Muhammad Rafiq
• Format: Thesis
• Language: English; English
• Published: 2024
• Online Access: http://eprints.utem.edu.my/id/eprint/29261/; https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=124402

Aluminium Silicon Carbide (AlSiC) metal matrix composites have gained significant attention due to their exceptional properties, combining the lightness of aluminum with the hardness and thermal conductivity of silicon carbide. However, machining AlSiC composites presents numerous challenges owing to their abrasive nature and the complexity of the machining process. Moreover, the lack of commercialization of a specific cutting tool for machining MMC materials is the source of several inherent problems such as rough machined surface and high cutting force. Addressing this matter, the development of a new cutter design specifically for machining MMC is necessitated. The objective of this study is to improve surface quality, machining force, and material removal rate. To achieve this, a comprehensive investigation was conducted involving the selection of appropriate cutting tools and the optimization of critical machining parameters, including cutting speed, feed rate, and depth of cut. Additionally, the effects of cutter geometrical features such as rake angle, clearance angle helix angle, and number of flutes were examined towards surface quality, machining force, and material removal rate. The experimental design was based on the Response Surface Methodology (RSM) design matrix, and machining tests were conducted using a CNC milling machine. Data obtained from these tests were analyzed using the Analysis of Variance (ANOVA), regression analysis, and desirability function approach. The results indicated significant interactions between machining parameters and tool geometries, highlighting the need for a systematic optimization approach. The optimized machining parameters and cutter geometrical features were validated through additional experiments, demonstrating remarkable improvements in improved surface finish, reduced cutting force, and higher material removal rate. Furthermore, the study provides valuable insights into the complex interplay between cutter geometrical features and machining parameters when dealing with AlSiC composites. In conclusion, this thesis offers a systematic approach to optimizing cutter geometrical features and machining parameters for AlSiC composite machining using RSM. The findings contribute to the advancement of machining processes for composite materials, particularly in industries where AlSiC composites find applications, such as aerospace and automotive. This research serves as a valuable resource for engineers and researchers seeking to enhance the efficiency and sustainability of AlSiC machining processes.