TY - GEN
T1 - Multi-objective Optimization-Driven Design
T2 - International Conference on Flexible Automation and Intelligent Manufacturing
AU - Daareyni, Amirmohammad
AU - Queguineur, Antoine
AU - Mokhtarian, Hossein
AU - Asadi, Reza
AU - Ituarte, Iñigo Flores
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - In recent years, advances in additive manufacturing (AM) technologies, particularly in Direct Energy Deposition (DED) as Wire Arc Additive Manufacturing (WAAM) and Laser Wire Directed Energy Deposition (LW-DED), have enabled engineers to produce large complex structures. Consequently, these developments drive a paradigm shift in how we conceptualize and manufacture complex components, pushing the limits of what is possible in engineering and design. As a result, there is a growing need for optimized structures considering the material constraints and advantages. This study uses a multi-objective optimization-driven engineering design approach to optimize the shape and materials of a train bogie as a case study. From the material perspective, different materials were selected to benefit from the high-strength steel (HSL) and low-carbon steel (LCS) and achieve weight reduction while considering other structural constraints. We generated multiple prospective designs using the generative design feature from Autodesk Fusion 360. Subsequently, safety factors are collected from these models using AbaqusCAE and the fatigue data with fe-safe. Moreover, a multi-objective optimization approach is applied to find the best possible design based on the resulting safety factor, weight, fatigue life, and maximum displacement of the proposed part. Finally, the collected results are compared, and a set of optimum designs is presented based on different criteria detailed in the study.
AB - In recent years, advances in additive manufacturing (AM) technologies, particularly in Direct Energy Deposition (DED) as Wire Arc Additive Manufacturing (WAAM) and Laser Wire Directed Energy Deposition (LW-DED), have enabled engineers to produce large complex structures. Consequently, these developments drive a paradigm shift in how we conceptualize and manufacture complex components, pushing the limits of what is possible in engineering and design. As a result, there is a growing need for optimized structures considering the material constraints and advantages. This study uses a multi-objective optimization-driven engineering design approach to optimize the shape and materials of a train bogie as a case study. From the material perspective, different materials were selected to benefit from the high-strength steel (HSL) and low-carbon steel (LCS) and achieve weight reduction while considering other structural constraints. We generated multiple prospective designs using the generative design feature from Autodesk Fusion 360. Subsequently, safety factors are collected from these models using AbaqusCAE and the fatigue data with fe-safe. Moreover, a multi-objective optimization approach is applied to find the best possible design based on the resulting safety factor, weight, fatigue life, and maximum displacement of the proposed part. Finally, the collected results are compared, and a set of optimum designs is presented based on different criteria detailed in the study.
KW - Additive Manufacturing
KW - Engineering design
KW - Generative design
KW - Multi-objective optimization
U2 - 10.1007/978-3-031-74485-3_6
DO - 10.1007/978-3-031-74485-3_6
M3 - Conference contribution
AN - SCOPUS:85213400423
SN - 9783031744846
T3 - Lecture Notes in Mechanical Engineering
SP - 48
EP - 55
BT - Flexible Automation and Intelligent Manufacturing
A2 - Wang, Yi-Chi
A2 - Chan, Siu Hang
A2 - Wang, Zih-Huei
PB - Springer
Y2 - 23 June 2024 through 26 June 2024
ER -