Deform 3D Simulation and Experimental Study in Machining of AISI 1020 Mild Steel

Abstract

The drilling process plays a crucial role in the assembly process of modern-day manufactories. One of the major causes of component rejection during drilling operations is the incorrect selection of spindle speed and feed rate. Therefore, this study aimed to investigate the impact of process factors such as spindle speed and feed rate on torque, thrust force, temperature surface roughness, and chip formation during the drilling of AISI 1020 mild steel. A combination of finite element modeling and experimental investigation was employed to achieve the process. Specifically, the commercially available finite element software, Deform 3D, was used for simulation. The modeling results were then compared and validated with the experimental data. A high-speed steel drill bit was utilized during the modeling and experimentation. The spindle speed was varied at 330, 410, and 510 rpm, while the feed rates were set at 0.12, 0.2, and 0.3 mm/rev. The study’s findings suggest that the spindle speed has an inverse relationship with thrust force, torque, and surface roughness, whereas it has a direct relationship with temperature. Conversely, the feed rate directly correlates with thrust force, torque, temperature, and surface roughness. Additionally, an analysis of the chips produced during the experiments revealed the impact of the cutting conditions on chip formation. The study results showed a 2–10% discrepancy between the experimental and simulation data. The ANOVA results indicated that the feed rate contributes the most to thrust force and torque, with a percentage contribution of 61.73% and 59.87%, respectively, followed by spindle speed, with a percentage contribution of 37.09% and 38.89%, respectively. Furthermore, temperature influences spindle speed the most, followed by feed rate, with percentage contributions of 67.75% and 31.11%, respectively. Moreover, the feed rate’s percentage contribution to surface roughness is higher than the spindle speed, with a contribution of 66.20% and 32.18%, respectively.

Publication DOI: https://doi.org/10.1155/2024/9085919
Divisions: College of Engineering & Physical Sciences > School of Engineering and Technology > Mechanical, Biomedical & Design
College of Engineering & Physical Sciences > Smart and Sustainable Manufacturing
Additional Information: Copyright © 2024 Aqib Hussain et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Publication ISSN: 2314-4912
Data Access Statement: Data will be made available by the corresponding author upon reasonable request.
Last Modified: 16 Jul 2024 07:28
Date Deposited: 19 Jun 2024 15:03
Full Text Link:
Related URLs: https://onlinel ... 55/2024/9085919 (Publisher URL)
PURE Output Type: Article
Published Date: 2024-05-27
Published Online Date: 2024-05-27
Accepted Date: 2024-05-18
Authors: Hussain, Aqib
Sharif, Aamer
Siddiqui, Muftooh Ur Rehman (ORCID Profile 0000-0002-7209-7863)
Hussain, Ghulam
Getachew, Melkamu Tadesse
Muhammad, Riaz

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