Cargando…

Experimental Analysis on the Influence and Optimization of μ-RUM Parameters in Machining Alumina Bioceramic

Fabrication of precise micro-features in bioceramic materials is still a challenging task. This is because of the inherent properties of bioceramics, such as low fracture toughness, high hardness, and brittleness. This paper places an emphasis on investigating the multi-objective optimization of fab...

Descripción completa

Detalles Bibliográficos
Autores principales: Abdo, Basem M. A., Anwar, Saqib, El-Tamimi, Abdulaziz M., Abouel Nasr, Emad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6416584/
https://www.ncbi.nlm.nih.gov/pubmed/30781711
http://dx.doi.org/10.3390/ma12040616
Descripción
Sumario:Fabrication of precise micro-features in bioceramic materials is still a challenging task. This is because of the inherent properties of bioceramics, such as low fracture toughness, high hardness, and brittleness. This paper places an emphasis on investigating the multi-objective optimization of fabrication of microchannels in alumina (Al(2)O(3)) bioceramics by using rotary ultrasonic machining (RUM). The influence of five major input parameters, namely vibration frequency, vibration amplitude, spindle speed, depth of cut, and feed rate on the surface quality, edge chipping, and dimensional accuracy of the milled microchannels was analyzed. Surface morphology and microstructure of the machined microchannels were also evaluated and analyzed. Unlike in previous studies, the effect of vibration frequency on the surface morphology and roughness is discussed in detail. A set of designed experiments based on central composite design (CCD) method was carried out. Main effect plots and surface plots were analyzed to detect the significance of RUM input parameters on the outputs. Later, a multi-objective genetic algorithm (MOGA) was employed to determine the optimal parametric conditions for minimizing the surface roughness, edge chipping, and dimensional errors of the machined microchannels. The optimized values of the surface roughness (Ra and Rt), side edge chipping (SEC), bed edge chipping (BEC), depth error (DE), and width error (WE) achieved through the multi-objective optimization were 0.27 μm, 2.7 μm, 8.7 μm, 8 μm, 5%, and 5.2%, respectively.