• International conference on construction engineering and project management
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• 2022.06a
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• pp.269-276
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• 2022

The robustness of a supply chain (i.e., the ability to cope with external and internal disruptions and disturbances) becomes more critical in ensuring the success of a construction project because the supply chain of today's construction project includes more and diverse suppliers. Previous studies indicate that topological features of the supply chain critically affect its robustness, but there is still a great challenge in characterizing and quantifying the impact of network topological features on its robustness. In this context, this study aims to identify network measures that characterize topological features of the supply chain and evaluate their impact on the robustness of the supply chain. Network centrality measures that are commonly used in assessing topological features in social network analysis are identified. Their validity in capturing the impact on the robustness of the supply chain was evaluated through an experiment using randomly generated networks and their simulations. Among those network centrality measures, the PageRank centrality and its standard deviation are found to have the strongest association with the robustness of the network, with a positive correlation coefficient of 0.6 at the node level and 0.74 at the network level. The findings in this study allows for the evaluation of the supply chain network's robustness based only on its topological design, thereby enabling practitioners to better design a robust supply chain and easily identify vulnerable links in their supply chains.

• Journal of the Korean Statistical Society
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• v.27 no.3
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• pp.331-348
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• 1998

In this paper, we have proposed some robust Bayes estimators using ML-II priors as well as certain empirical Bayes estimators in estimating the finite population mean in the presence of auxiliary information. These estimators are compared with the classical ratio estimator and a subjective Bayes estimator utilizing the auxiliary information in terms of "posterior robustness" and "procedure robustness" Also, we have addressed the issue of choice of sampling design from a robust Bayesian viewpoint.

• International Journal of Aerospace System Engineering
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• v.2 no.2
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• pp.67-72
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• 2015

The main concern of this study is to integrate the EARSM into an industrial RANS solver in conjunction with the $k-{\omega}$ model, as proposed by Hellsten (EARSMKO2005). In order to improve the robustness, particular limiters are introduced to turbulent conservative variables, and a suitable full-approximation storage (FAS) multi-grid (MG) strategy is designed to incorporate turbulence model equations. The present limiters and MG strategy improve both robustness and efficiency significantly but without degenerating accuracy. Two discretization approachs for velocity gradient on cell interfaces are implemented and compared with each other. Numerical results of a three-dimensional supersonic square duct flow show that the proper discretization of velocity gradient improves the accuracy essentially. To assess the capability of the resulting EARSM $k-{\omega}$ model to predict complex engineering flow, the case of Common Research Model (CRM, Wing-Body) is performed. All the numerical results demonstrate that the resulting model performs well and is comparable to the standard two-equation models such as SST $k-{\omega}$ model in terms of computational effort, thus it is suitable for industrial applications.

• Geomechanics and Engineering
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• v.22 no.4
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• pp.305-318
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• 2020

Stone columns are widely used to treat soft clay ground. Optimizing the design of stone columns based on cost-effectiveness is always an attractive subject in the practice of ground treatment. In this paper, the design of stone columns is optimized using the concept of robust geotechnical design. Standard deviation of failure probability, which is a system response of concern of the stone column-reinforced foundation, is used as a measure of the design robustness due to the uncertainty in the coefficient of variation (COV) of the noise factors in practice. The failure probability of a stone column-reinforced foundation can be readily determined using Monte Carlo simulation (MCS) based on the settlements of the stone column-reinforced foundation, which are evaluated by a deterministic method. A framework based on the concept of robust geotechnical design is proposed for determining the most preferred design of stone columns considering multiple objectives including safety, cost and design robustness. This framework is illustrated with an example, a stone column-reinforced foundation under embankment loading. Based on the outcome of this study, the most preferred design of stone columns is obtained.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.1
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• pp.17-24
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• 2004

This paper proposes an optimal robust LQ-PID controller design method for the second order systems to satisfy the design specifications in time domain. The tuning parameters of LQ-PID controller are determinated by the relationships between the design parameters of the overshoot and the settling time which are design specifications in time domain, and the weighting factors Q and R in LQR. we can achieve the performance-robustness in time domain as well as the stability-robustness.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.1 s.173
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• pp.215-224
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• 2000

In order to reduce the variation effects of uncertainties in the engineering environments, new robust optimization method, which considers the uncertainties in design process, is proposed. Both design variables and system parameters are considered as random variables about their nominal values. To ensure the robustness of performance function, a new objective is set to minimize the variance of that function. Constraint variations are handled by introducing probability constraints. Probability constraints are solved by the advanced first order second moment (AFOSM) method based on the reliability theory. The proposed robust optimization method has an advantage that the second derivatives of the constraints are not required. The suggested method is examined by solving three examples and the results are compared with those for deterministic case and those available in literature.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.4
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• pp.270-276
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• 2003

The disturbance observer (DOB) has been widely utilized fer high precision and high speed motion control application. However, it still lacks the analysis for the robustness brought by using DOB. This paper summarizes six guidelines for the design of DOB taking into account the robustness and control performance in case of the second order system. For effectiveness of the proposed guideline, the actual implementation and experimental results of the DOB is compared in the Optical Disk Drive(ODD) servo system. In the DVD player and DVD-ROM drive, the guidelines of DOB are useful, and the disturbance rejection performance is improved under the DOB system.

• Journal of Communications and Networks
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• v.16 no.3
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• pp.264-269
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• 2014

We consider transmission over body area networks. Due to the difficulty in assessing an accurate statistical model valid for multiple scenarios, we advocate a system design technique favoring robustness. Our approach, which is based on results in [12] and generalizes them, examines the variation of a performance metric when the nominal statistical distribution of fading is replaced by the worst distribution within a given Kullback-Leibler divergence from it. The sensitivity of the performance metric to the divergence from the nominal distribution can be used as an indication of the design robustness. This concept is applied by evaluating the error probability of binary uncoded modulation and the outage probability-the first parameter is useful to assess system performance with no error-control coding, while the second reflects the performance when a near-optimal code is used. The usefulness of channel coding can be assessed by comparing its robustness with that of uncoded transmission.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.455-460
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• 1998

We propose robust MILP model for scheduling and design of multiproduct batch processes in this paper. Recent stochastic modeling approaches considering uncertainty have mainly focused on maximization of expected NPV. Robust model concept is applied to generate solution spectrum in which we can select the best solution based on tradeoff between robustness measure and expected NPV. Robustness measure is represented as penalty term in the objective function, which is Upper Partial Mean of NPV. We can quantify solution robustness by this penalty term and maintain model as MILP form to be computationally efficient. An example illustrates the effectiveness of the proposed model. In many cases sufficient robustness can be guaranteed through a little reduction of expected NPV.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1254-1261
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• 2003

In this paper we present a simple and efficient robust optimal design formulation and its application to a resonant-type micro probe. The basic idea is to use the Gradient Index (GI) to improve robustness of the objective and constraint functions. In the robust optimal design procedure, a deterministic optimization for performance of MEMS structures is followed by design sensitivity analysis with respect to uncertainties such as fabrication errors and change of operating conditions. During the process of deterministic optimization and sensitivity analysis, dominant performance and uncertain variables are identified to define GI. The GI is incorporated as a term of objective and constraint functions in the robust optimal design formulation to make both performance and robustness improved. While most previous approaches for robust optimal design require statistical information on design variations, the proposed GI based method needs no such information and therefore is cost-efficient and easily applicable to early design stages. For the micro probe example, robust optimums are obtained to satisfy the targets for the measurement sensitivity and they are compared in terms of robustness and production yield with the deterministic optimums through the Monte Carlo simulation.