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Today, consumers of the vehicle want to drive a good steering feel car which has direct vehicle response and linear steering feedback during cornering. Almost all of the magazine experts give the good steering feel cars high marks and recommend those cars to consumers. The purpose of this study is to improve steering feel using suspension parameters. The suspension parameters govern the motion of the vehicle. These parameters are various and have relations with each other. So we need to a clever method to analyze multivariate data. It is necessary to apply MTS (Mahalanobis Taguchi System) method which is a diagnosis and forecasting method for multivariate data. The first thing of design suspension parameters is that analyze the suspension parameters using SPMD(Suspension Parameter Measure Device). After analyzing some data of the SPMD, we diagnose the test car with competitive cars by using MTS. MD (Mahalanobis Distance) is a measure based on correlations between the variables and different patterns that can be identified and analyzed with respect to a base or reference group. So we can identify the level of the test car against competitive cars by using MD. Through diagnosing test car, we study the cause of the insufficiency of the steering feel and find out the suspensions parameters that should improve for the steering feel. Finally we can study the robust design(DFSS) about the steering feel base on the MTS

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Abstract
1. 서론
2. 본론
3. 현가장치 강건설계
4. 결론
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UCI(KEPA) : I410-ECN-0101-2009-556-015698622