Multi Objective Performance Optimization Of Hybrid Rotary Ultrasonic Assisted End Milling For Machining Hardened Steel Material

• 主要作者: Ramli, Azlan
• 格式: Thesis
• 語言: 英语; 英语
• 出版: 2020
• 主題: T Technology (General); TJ Mechanical engineering and machinery
• 在線閱讀: http://eprints.utem.edu.my/id/eprint/25409/; https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=119770

Hardened D2 tool steel is widely used in the mold and die industry especially for injection molding tools, cold forming tools and precision engineering parts. Most of the applications require an excellent surface finish as it will reflect on the end product appearance. However, the high strength of these materials (>50 HRC) results in rough machined surface when using the conventional machining process, hence, special machining technique is required to maintain the part quality. In current industry practice, the machining tolerances are generally achieved by subsequent manual finishing process such as, polishing and grinding in order to realize both the required geometry and surface finish. Notably, the aforementioned manufacturing techniques for mould and die fabrication tend to decrease productivity and create uncertainty over the component accuracy. Hence, this thesis proposed a significant advancement on improving the mould fabrication process using a hybrid machining technique such as, combining two established machining processes into a new combined set-up known as Rotary Ultrasonic Assisted End Milling (RUAEM) whereby the advantages of each discrete process could be exploited synergistically. A total of 162 experimental runs based on statistical Response Surface Methodology matrix were executed comprising different level of machining parameter namely cutting speed, feed rate, depth of cut, frequency of vibration, amplitude vibration and alumina oxide slurry concentration towards surface roughness, cutting force and material removal rate. The investigation proceeded until a set of optimal machining parameter and satisfactory validation index were achieved. Based on the recommended optimized model, the best achievable surface roughness (Ra), resultant force (FR) and material removal rate (MRR) values was 0.12 µm, 4.98 N and 161.58 mg/min respectively. The results yielded that RUAEM process was able to improve 97% of the surface roughness, 92% of cutting force magnitude and 26% of material removal rate in comparison to the conventional machining processes within the same cutting conditions. For the multiple response optimization result, the combination of 111.45 rpm, 5.75 mm/min feed rate, 27.05 µm depth of cut, 20.91 kHz vibration frequency, 3 µm amplitude and 13.26% abrasive concentration yielded the highest desirability index of 0.87. Lastly, a good agreement value between the prediction and experimental validate the new proposed parameter optimization.