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All Journal Journal of Mechanical Engineering, Science, and Innovation
Aulia, Muhammad Najmul
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Control & Systems Engineering Energy Engineering Mechanical Engineering

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Comparison of Manual, AI Generative, and Hybrid Design on Structural Performance and Manufacturing Aspects of Truck Wheel Mounting Aid Frame using FEA in Fusion 360 Aulia, Muhammad Najmul; Nugroho, Dony Satriyo
Journal of Mechanical Engineering, Science, and Innovation Vol 6, No 1 (2026): (April)
Publisher : Institut Teknologi Adhi Tama Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.jmesi.2026.v6i1.8749

Abstract

This study compares the structural performance of a truck wheel installation assist frame designed using three approaches: manual design, generative AI design, and hybrid design. The analysis was carried out using Finite Element Analysis (FEA) in Autodesk Fusion 360 with Stainless Steel AISI 304 as the material and a static load of 2,500 N. Performance evaluation was based on von Mises stress, total deformation, and safety factor relative to the material’s yield strength. The simulation results show that the manual design produces a maximum stress of 106.581 MPa, a deformation of 2.557 mm, and a safety factor of 2.017. The generative AI design shows a maximum stress of 1,818.205 MPa, a deformation of 65.634 mm, and a safety factor of 0.118, indicating structural failure. Meanwhile, the hybrid design demonstrates the best performance with a maximum stress of 101.904 MPa, a deformation of 1.664 mm, and a safety factor of 2.11. Therefore, the hybrid design is considered the most suitable option, as it achieves a balance between mass efficiency, structural stiffness, and manufacturability for practical workshop applications. 
Co-Authors Nugroho, Dony Satriyo