Tolerance Optimization of Design Variables in Lower Arm by Using Response Surface Model and Process Capability Index

2013 ◽  
Vol 18 (5) ◽  
pp. 359-366
Author(s):  
Kwang Ki Lee ◽  
Yun Cheol Ro ◽  
Seung Ho Han
2009 ◽  
Vol 419-420 ◽  
pp. 89-92
Author(s):  
Zhuo Yi Yang ◽  
Yong Jie Pang ◽  
Zai Bai Qin

Cylinder shell stiffened by rings is used commonly in submersibles, and structure strength should be verified in the initial design stage considering the thickness of the shell, the number of rings, the shape of ring section and so on. Based on the statistical techniques, a strategy for optimization design of pressure hull is proposed in this paper. Its central idea is that: firstly the design variables are chosen by referring criterion for structure strength, then the samples for analysis are created in the design space; secondly finite element models corresponding to the samples are built and analyzed; thirdly the approximations of these analysis are constructed using these samples and responses obtained by finite element model; finally optimization design result is obtained using response surface model. The result shows that this method that can improve the efficiency and achieve optimal intention has valuable reference information for engineering application.


2014 ◽  
Vol 551 ◽  
pp. 232-236
Author(s):  
Tian Ze Shi ◽  
Deng Feng Wang ◽  
Shu Ming Chen ◽  
Hong Liang Dong

A double pivot suspension used for in-wheel motor electric vehicle was designed, and the virtual prototype model of the suspension assembly was build. The suspension parameters changed greatly during steering. In order to solve this problem, this paper proposed a non-linear response surface model to fit the relationship of suspension parameters and design variables. An optimization scheme was designed based on the response surface model. The suspension performance was improved significantly using optimized variables.


Author(s):  
Sudhir Kaul ◽  
Anoop K. Dhingra

This paper presents a Response Surface Modeling (RSM) approach for solving the engine mount optimization problem for a motorcycle application. A theoretical model that captures the structural dynamics of a motorcycle engine mount system is first used to build the response surface model. The response surface model is then used to solve the engine mount optimization problem for enhanced vibration isolation. Design of Experiments (DOE), full factorial and fractional factorial formulations, are used to construct the governing experiments. Normal probability plots are used to determine the statistical significance of the variables and the significant variables are then used to build the response surface. The design variables for the engine mount optimization problem include mount stiffness, position vectors and orientation vectors. It is seen that RSM leads to a substantial reduction in computational effort and yields a simplified input-output relationship between the variables of interest. However, as the number of design variables increases and as the response becomes irregular, conventional use of RSM is not viable. Two algorithms are proposed in this paper to overcome the issues associated with the size of the governing experiments and problems associated with modeling of the orientation variables. The proposed algorithms divide the design space into sub-regions in order to manage the size of the governing experiments without significant confounding of variables. An iterative procedure is used to overcome high response irregularity in the design space, particularly due to orientation variables.


Author(s):  
Zhixun Yang ◽  
Jun Yan ◽  
Svein Sævik ◽  
Luqing Zhen ◽  
Naiquan Ye ◽  
...  

An optimized flexible riser design not only requests that the stress of local cross-section shouldn’t exceed the allowable strength, but also can be compliant with the floater to improve the fatigue life. It should be particularly pointed out that the flexible riser is a typical multi-scale system, which consists of the local cross-sectional scale and the global configuration scale, which differentiates each other a lot from their geometrical scales. A bi-scale response surface model is established to perform the optimized design of flexible risers by considering the parameters of local cross-sections and global configurations simultaneously. The response surface model can be an effective surrogate model to integrate the local and global responses into one loop so that the computational efficiency can be increased significantly. In the bi-scale response model, design variables of a flexible riser are extracted and defined at both the local sectional scale and global configuration scale. Sensitivity analyses of the two objectives, ultimate tension and bending strength on the design variables are then deduced to establish the bi-scale optimization framework through the response surface methodology. Finally, the optimization framework is implemented on a flexible riser with lazy-wave configuration which is considered as a case study. The properties of the optimized flexible risers are compared with those without the optimization. It is found that the ultimate load bearing capacity and fatigue life of the optimized flexible riser are improved significantly. Moreover, the feasibility and effectiveness of the bi-scale optimization strategy are verified through numerical simulations, which indicates that the bi-scale response surface optimization methodology provides a new thought and approach to explore the design potential of flexible risers.


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