Robust design of lower arm suspension using stochastic optimization method / Mohd Khairil Azirul Bin Khairolazar
Material type:
TextPublication details: Kuantan, Pahang : UMP, 2009Description: xiii, 32 p. : ill. (some col.) ; 30 cm. + 1 computer discISBN: - THE0007283(Local)
- Robust design of lower arm suspension using stochastic optimization method [electronic resource]
| Item type | Current library | Call number | Copy number | Status | Date due | Barcode | |
|---|---|---|---|---|---|---|---|
Final Year Report
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UMPLIB PEKAN | TL257 .K43 2009 rs Bc. (Browse shelf(Opens below)) | 1 | Not for loan | 0000044279 | ||
Final Year Report
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UMPLIB PEKAN | CD 4163 | TL257 .K43 2009 rs Bc. (Browse shelf(Opens below)) | 1 | Not for loan | 0000044280 |
Project paper (Bachelor of Mechanical Engineering with Automotive Engineering) -- Universiti Malaysia Pahang - 2009
This project presents the development of robust design of lower suspension arm using stochastic optimization. The strength of the design analyze by finite element software. The structural model of the lower suspension arm was mode by using the solidworks. The finite element model and analysis were performed utilizing the finite element analysis code. The linear elastic analysis was performed using NASTRAN codes. TET10 and TET4 mesh has been used in the stress analysis and the highest Von Mises stress of TET10 has been selected for the robust design parameter. The development of Robust design was carried out using the Monte Carlo approach, which all the optimization parameter for the design has been optimized in Robust design software. The improvements from the Stochastic Design Improvement (SDI) are obtained. The design capability to endure more pressure with lower predicted stress is identified through the SDI process. A lower density and modulus of elasticity of material can be reconsidered in order to optimize the design. The area of the design that can be altered for the optimization and modification is identified through the stress analysis result. As a conclusion, the robust design by using stochastic optimization was capable to optimize the lower arm suspension. Thus, all the result from this project can be use as guideline before developing the prototype.