• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.7
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• pp.1243-1250
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• 2003

In the present study, hot forging process for a lower arm connector of an automobile was investigated. An FEM code, DEFORM-3D, was used to analyze the process and the process parameters, such as temperature, strain and strain rate, were obtained. The microstructure of the connector was predicted by applying the Sellars and Yada microstructure evolution models to the process parameters. The method of microstructure prediction used in the present study seems to be effective for the quality assurance of a forged automotive product.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.1
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• pp.126-134
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• 2014

This study investigates the structural strength analysis due to rib thickness of lower arm. At structural analysis, model 1 has the most deformation by comparing three models. As most equivalent stress is shown at the part connected with wheel knuckle, the strength becomes weaker in cases of three models. At fatigue analysis, model 1 becomes most unstabilized among three models. Model 3 has most fatigue life and the next model is model 2. The range of maximum harmonic response frequencies becomes 140 to 175Hz in cases of three models. Because the critical frequency at model 3 becomes highest among three models but the stress exceeds yield stress, model 3 becomes most unstabilized at vibration durability. As models 1 and 2 has less than yield stress, these models become stabilized. Model 2 becomes most favorable by comparing three models at structural, fatigue and vibration analyses. This study result can be effectively utilized with the design of lower arm by investigating prevention against damage and its strength durability.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.6
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• pp.29-34
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• 2017

This study analyzed automobile lower arm assembly structure and fatigue to identify configuration changes to enhance structural safety. Parts connected to the car body were fixed and 500 N load was applied at the lower arm head. Maximum equivalent stress and maximum total deformation were minimized for model 1 ( MPa and 0.10315 mm, respectively). Fatigue analysis using extreme SAE bracket history fatigue loads showed model 1 also improved fatigue life ($3.3693{\times}10^5cycles$). This study provides important inputs to improve lower arm durability by modifying the arm configuration.

• Korean Journal of Computational Design and Engineering
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• v.18 no.5
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• pp.359-366
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• 2013

In the lower arm design process, a tolerance optimization of the variance of design variables should be preceded before manufacturing process, since it is very cost-effective compared to a strict management of tolerance of products. In this study, a design of experiment (DOE) based on response surface model (RSM) was carried out to find optimized design variables of the lower arm, which can meet a given requirement of probability constraint for the process capability index (Cpk) of the weight and maximum stress. Then, the design space was explored by using the central composite design method, in which the 2nd order Taylor expansion was applied to predict a standard deviation of the responses. The optimal solutions satisfying the probability constraint of the Cpk were found by considering both of the mean value and the standard deviation of the design variables.

• Journal of Korea Foundry Society
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• v.28 no.5
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• pp.231-236
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• 2008

H-NCM(Hong-Nanocast Method)has several benefits such as a lower porosity defect and high quality casting comparing to conventional die casting. Influence of casting parameters of hybrid-lower arm in rheocasting process on the slurry flow and the amount of porosity defect was investigated using experimental and simulation methods. In the present study, the Carreau model was adopted to simulate the pattern of rheological flow. Optimal casting paremeters such as injection speed and stroke variations were established. Sound products with integral microstructure and sound shape of joinning different materials of Al and steel pipe without deforming the steel pipe were obtained by the H-NCM slurry and X-ray analysis also showed integral condition throughout the entire parts.

• Korean Journal of Computational Design and Engineering
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• v.11 no.1
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• pp.49-56
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• 2006

In this study, the modeling support system was developed which can make easy and fast FE-modeling and verify the results of static and durability analysis for the lower arm, one of the important parts in automobile suspension module. It took into account of the whole complicated design processes verifying the durability coefficients evaluated by fatigue analysis, which should be used to satisfy a design criteria. To guide the FE-modeling the drive page was constructed by using HTML and XML, which was based on expert's know-hows. It is able to integrate the processes to design the lower arm in practice, so that the standardization of its FE-Modeling is achieved, consequently. The 3 dimensional CAD's geometrical data were changed automatically into pre-defined shell elements under the concept of mesh-offset technique, and then welding elements were treated to connect between target and basic surfaces constructed by the shell elements. This system has also a user interface to control boundary and load ing conditions applied in performing of the static and durability analysis, in which many load cases can be applied simply with the MPCs driven by just few mouse clicks. These were implemented on the platform of MSC.Patran and utilized ANSYS, MSC.Nastran and MSC.Fatigue as the solver of the analysis performed. The developed system brings not only significant decreasing of man-hours required in FE-modeling process, but also obtaining of satisfied qualities in analyzed results. It will be integrated in a part of virtual prototyping module of the developing e-engineering framework.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.4
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• pp.482-489
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• 2011

In practical design process, designer needs to find an optimal solution by using full factorial discrete combination, rather than by using optimization algorithm considering continuous design variables. So, ANOVA(Analysis of Variance) based on an orthogonal array, i.e. Taguchi method, has been widely used in most parts of industry area. However, the Taguchi method is limited for the shape optimization by using CAE, because the multi-level and multi-objective optimization can't be carried out simultaneously. In this study, a combined method was proposed taking into account of multi-level computational orthogonal array and TOPSIS(Technique for Order preference by Similarity to Ideal Solution), which is known as a classical method of multiple attribute decision making and enables to solve various decision making or selection problems in an aspect of multi-objective optimization. The proposed method was applied to a case study of the multi-level shape optimization of lower arm used to automobile parts, and the design space was explored via an efficient application of the related CAE tools. The multi-level shape optimization was performed sequentially by applying both of the neural network model generated from seven-level four-factor computational orthogonal array and the TOPSIS. The weight and maximum stress of the lower arm, as the objective functions for the multi-level shape optimization, showed an improvement of 0.07% and 17.89%, respectively. In addition, the number of CAE carried out for the shape optimization was only 55 times in comparison to full factorial method necessary to 2,401 times.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.10
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• pp.1323-1328
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• 2011

In the current design process for the lower arm used in automobile parts, an optimal solution of its various design variables should be found through exploration of the design space approximated using the response surface model formulated with a first- or second-order polynomial equation. In this study, a multi-level computational DOE (design of experiment) was carried out to explore the design space showing nonlinear behavior, in terms of factors such as the total weight and applied stress of the lower arm, where a fractional-factorial orthogonal array based on the artificial neural network model was introduced. In addition, the tolerance robustness of the optimal solution was estimated using a tolerance optimization with six sigma constraints, taking into account the tolerances occurring in the design variables.