Assembly Variation Analysis of Incompletely Positioned Macpherson Suspension Systems Considering Vehicle Load Change

Niu, Zhihua; Jin, Sun; Li, Zhimin

doi:10.1115/1.4048413

Cited by 6 publications

(5 citation statements)

References 25 publications

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“…The next generation of geometrical variation management can be described as a number of activities to minimize the geometric variation in the final product [11]. This could be achieved by optimizing the manufacturing process or using design-stage simulation.…”

Section: Related Workmentioning

confidence: 99%

“…Thus, the dimension of [u, v, w] is a translation vector and [α, β, γ] is a rotation vector compared with the nominal elements. Different tolerance types correspond to different SDTI [11,38,39]. For a detailed explanation the meaning of these symbols, the SDTI for flatness tolerance and concentricity are shown in Table 2 [36].…”

Section: Definition Of the Node Representation Based On Thementioning

confidence: 99%

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A Data-Driven Methodology to Improve Tolerance Allocation Using Product Usage Data

Gao

Zheng

et al. 2021

Journal of Mechanical Design

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Industry 4.0 puts forward new requirements for the sustainable service of products. With the recent advances in measurement technologies, global and local deformations in inaccessible areas can be monitored. Product usage data such as geometric deviation, position deviation and angular deviation that lead to product functional performance degradation can be continuously collected during the product usage stage. These technologies provide opportunities to improve tolerance design by optimizing tolerance allocation using product usage data. The challenge lies in how to assess these deviations for identifying relevant field factors and reallocate the tolerance value. In this paper, a data-driven methodology based on the deviation for tolerance analysis is proposed to optimize the tolerance allocation. A feature graph of a mechanical assembly is established based on the assembly relationship. The node representation in the feature graph is defined based on the unified Jacobian-torsor model and the node label is calculated by a synthetic evaluation method. A novel algorithm based on the graph neural networks (GNNs) is proposed to investigate hidden relations between nodes in the feature graph and calculate labels of all nodes. A modification necessity index (MNI) is defined for each tolerance between two nodes based on their labels. A deviation difference matrix is constructed to calculate the MNI of each tolerance for identifying the to-be-modified tolerance value with high priorities for product improvement. The effectiveness of the proposed methodology is demonstrated through a case study for the optimal tolerance allocation of a press machine.

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Section: Related Workmentioning

confidence: 99%

Section: Definition Of the Node Representation Based On Thementioning

confidence: 99%

A Data-Driven Methodology to Improve Tolerance Allocation Using Product Usage Data

Gao

Zheng

et al. 2021

Journal of Mechanical Design

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“…In Eskandari et al (2006), the response surface methodology as a design of experiment is used to optimize a full car model to obtain better behavior on steering. In addition, Niu et al (2021) provide a solid and applied study in the assembly of McPherson suspension mechanism; however, their study did not include optimization but it covered an extension to the existed method. This research has employed the ADAMS software for validation process as well.…”

Section: Introductionmentioning

confidence: 99%

Constraint optimization of nonlinear McPherson suspension system using genetic algorithm and ADAMS software

Vahedi

Jamali

2021

Journal of Vibration and Control

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In this article, optimization of the McPherson suspension mechanism of a real car named Arisan is considered. In this regard, a model based on a real-life suspension system is proposed with the least simplification. This model is built in the ADAMS/View software based on the actual size of the suspension mechanism of Arisan. Moreover, the user-written code of the genetic algorithm in C is added as a plug-in to the ADAMS/View software in a completely innovative way to optimize the suspension system. 16 parameters of the suspension system are selected as design variables to wholly handle its geometry. The value of all design variables is optimally found by GA to minimize the variation of the camber angle as an objective function. Comparison of the obtained optimum suspension by the proposed method with the actual suspension system of Arisan shows a 23.5% improvement in the camber variation angle. It is worth noting that the proposed method does not require a mathematical model of the suspension system that leads to some simplifications such as linearization and non-friction joints. The proposed method can be used for modeling and optimization of other nonlinear dynamical systems such as robotics and building structures.

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“…Shi and Zhang 18 proposed an improved Support Vector Machine (SVM) algorithm to diagnosis the faults of vehicle steering systems. Niu et al 19,20 improved the assembly precision of wheel alignment parameters through tolerance propagation analysis.…”

Section: Introductionmentioning

confidence: 99%

Geometry optimization of a planar double wishbone suspension based on whole-range nonlinear dynamic model

Niu

Jin

Wang

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part D:

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Dynamic analysis is an essential task in the geometry design of suspension systems. Whereas the dynamic simulation based on numerical software like Adams is quite slowly and the existing analytical models of the nonlinear suspension geometry are mostly based on small displacement hypothesis, this paper aims to propose a whole-range dynamic model with high computational efficiency for planar double wishbone suspensions and further achieve the fast optimal design of suspension geometry. Selection of the new generalized coordinate and explicit solutions of the basic four-bar mechanism dramatically reduce the complexity of suspension geometry representation and provide analytical solutions for all of the time varying dimensions. By this means, the running speed and computational accuracy of the new model are guaranteed simultaneously. Furthermore, an original Matlab/Simulink implementation is given to maintain the geometric nonlinearity in the solving process of dynamic differential equations. After verifying its accuracy with an ADAMS prototype, the presented whole-range model is used in the vast-parameter optimization of suspension geometry. Since both kinematic and dynamic performances are evaluated in the objective function, the optimization is qualified to give a comprehensive suggestion to the design of suspension geometry.

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Assembly Variation Analysis of Incompletely Positioned Macpherson Suspension Systems Considering Vehicle Load Change

Cited by 6 publications

References 25 publications

A Data-Driven Methodology to Improve Tolerance Allocation Using Product Usage Data

A Data-Driven Methodology to Improve Tolerance Allocation Using Product Usage Data

Constraint optimization of nonlinear McPherson suspension system using genetic algorithm and ADAMS software

Geometry optimization of a planar double wishbone suspension based on whole-range nonlinear dynamic model

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