Browsing by Author "Nurhusien Hassen"

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    Optimization of Machining Parameters in Drilling Hybrid Sisal – Cotton Fiber Reinforced Polyester Composite
    (Addis Ababa University, 2021-07) Nurhusien Hassen; Desalegn Wogaso (PhD)
    As compared to metals, composite materials machining is a challenge because the cutting tool needs to move through the matrix and fiber alternately, which have various properties. The objective of this work is to optimize the machining parameters in drilling hybrid sisal-cotton fiber reinforced polyester composite (HSCFRPC) to reduce the hole roundness error and surface roughness using Taguchi's method. The influence of machining parameters such as spindle speed, drill diameter, and feed rate on the surface roughness and roundness error of HSCFRPC during the drilling process on the vertical CNC milling machine have been analyzed using the methods of Taguchi’s design of experiment. A series of experiments based on 𝐿16 orthogonal arrays were established with different feed rates (10, 15, 20, 25 mm/min), spindle speeds (600, 900, 1200, 1600rpm), and drill diameter (6, 7, 8, 10mm). The measurement of roundness error and surface roughness have been carried out using ABC digital caliper and Zeta 20 profilometer respectively. The experimental values are gathered and analyzed using the MINITAB 19 commercial software program. To create a connection between the chosen drilling parameters and the quality attributes of the drilled holes, linear regression equations have been established. Signal to noise (S/N) ratio analysis and analysis of variance (ANOVA) were performed to identify the rank, percentage contribution and optimum values of these machining parameters such as spindle speed, drill diameter, and feed rate to reduce the roundness error and surface roughness. Based on the analysis the best combination of the optimum machining parameter values (1600rpm, 25 mm/min, and 6mm) are selected to reduce both roundness error and surface roughness of the composite. Finally, verification of the recommended machining parameters have been achieved and the values of roundness error and surface roughness obtained are 0.1mm and 64.8μm Ra respectively, which satisfies the objective of lowest roundness error and surface roughness. The verification result shows that the recommended machining parameter values to reduce roundness error and surface roughness based on Taguchi’s analysis were precise and fitted to the optimum values.