Search Results - "Rivera, D.E."

Model Predictive Control for Tactical Decision-Making in Semiconductor Manufacturing Supply Chain Management by Wenlin Wang, Rivera, D.E.

“…Supply chain management (SCM) in semiconductor manufacturing poses significant challenges that arise from the presence of long throughput times, unique…”
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A hierarchical approach to production control of reentrant semiconductor manufacturing lines by Vargas-Villamil, F.D., Rivera, D.E., Kempf, K.G.

“…A three-layer hierarchical approach for inventory control and production optimization of semiconductor reentrant manufacturing lines is developed. At the top…”
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Simulation of Semiconductor Manufacturing Supply-Chain Systems With DEVS, MPC, and KIB by Dongping Huang, Sarjoughian, H.S., Wenlin Wang, Godding, G., Rivera, D.E., Kempf, K.G., Mittelmann, H.

“…The dynamics of high-volume discrete-part semiconductor manufacturing supply-chain systems can be described using a combination of Discrete EVent System…”
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Control-Relevant Demand Forecasting for Tactical Decision-Making in Semiconductor Manufacturing Supply Chain Management by Schwartz, J.D., Arahal, M.R., Rivera, D.E., Smith, K.D.

“…Forecasting highly uncertain demand signals is an important component for successfully managing inventory in semiconductor supply chains. We present a…”
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Hyperglycemia reduces functional expression of astrocytic Kir4.1 channels and glial glutamate uptake by Rivera-Aponte, D.E, Méndez-González, M.P, Rivera-Pagán, A.F, Kucheryavykh, Y.V, Kucheryavykh, L.Y, Skatchkov, S.N, Eaton, M.J

“…Highlights • The effect of hyperglycemia on astrocytic potassium channel function was studied. • Hyperglycemia decreases astrocytic Kir4.1 mRNA and protein…”
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An integrated identification and control design methodology for multivariable process system applications by Rivera, D.E., Jun, K.S.

“…We present a way to take advantage of the favorable asymptotic properties of ARX estimators to develop an integrated methodology for identification and…”
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Digital PID controller design using ARX estimation by Rivera, D.E., Gaikwad, S.V.

“…This paper describes a comprehensive methodology to obtain reduced-order models that satisfy the Prett-Garcia digital PID tuning rules, using prefiltered…”
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An interactive software tool for system identification by Guzmán, J.L., Rivera, D.E., Dormido, S., Berenguel, M.

“…The paper describes the conceptual basis, main features and functionality of an interactive software tool developed in support of system identification…”
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Perspectives on control-relevant identification through the use of interactive tools by Álvarez, J.D., Guzmán, J.L., Rivera, D.E., Berenguel, M., Dormido, S.

“…System identification is an essential part of control design. Control engineers must devote substantial effort to identification issues in order to obtain…”
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A computer-aided design tool for robustness analysis and control-relevant identification of Horizon Predictive Control with application to a binary distillation column by Jun, K.S., Rivera, D.E., Elisante, E., Sater, V.E.

“…This paper describes a MATLAB-based computer-aided design tool, IRA-HPC, which accomplishes integrated system identification and robustness analysis for…”
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A Model Predictive Control framework for robust management of multi-product, multi-echelon demand networks by Braun, M.W., Rivera, D.E., Flores, M.E., Carlyle, W.M., Kempf, K.G.

“…Model Predictive Control (MPC) is presented as a robust, flexible decision framework for dynamically managing inventories and meeting customer requirements in…”
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Application of minimum crest factor multisinusoidal signals for “plant-friendly” identification of nonlinear process systems by Braun, M.W., Ortiz-Mojica, R., Rivera, D.E.

“…Guidelines for specifying the design parameters of minimum crest factor multisine signals generated per the approach of Guillaume et al. are presented. These…”
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Towards control-relevant forecasting in supply chain management by Schwartz, J.D., Rivera, D.E., Kempf, K.G.

“…The focus of this paper is understanding the effects of demand forecast error on a tactical decision policy for a single node of a manufacturing supply chain…”
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Interaction of N-nitrosodiethylamine/bovine serum albumin complexes with 1,2-dipalmitoyl-sn-glycero-3-phosphocholine monolayers at the air–water interface by Valencia-Rivera, D.E., Básaca-Loya, A., Burboa, M.G., Gutiérrez-Millán, L.E., Cadena-Nava, R.D., Ruiz-García, J., Valdez, M.A.

“…We report the effect of N-nitrosodiethylamine (NDA) on the interaction between bovine serum albumin (BSA) and 1,2-dipalmitoyl-sn-glycero-3-phosphocholine…”
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PID Control: New Identification and Design Methods - [Book Review] by Rivera, D.E.

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High-Purity Distillation by Rivera, D.E., Hyunjin Lee, Mittelmann, H.D., Braun, M.W.

“…Distillation is one of the most common separation techniques in chemical manufacturing. This multi-input, multi-output staged separation process is strongly…”
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Hybrid discrete event simulation with model predictive control for semiconductor supply-chain manufacturing by Sarjoughian, H.S., Dongping Huang, Godding, G.W., Wenlin Wang, Rivera, D.E., Kempf, K.G., Mittelmann, H.D.

“…Simulation modeling combined with decision control can offer important benefits for analysis, design, and operation of semiconductor supply-chain network…”
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Flexible Experimentation and Analysis for Hybrid DEVS and MPC Models by Dongping Huang, Sarjoughain, H.S., Godding, G.W., Rivera, D.E.

“…Discrete-event simulation and control-theoretic approaches lend themselves to studying semiconductor manufacturing supply-chain systems. In this work, we…”
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An integrated input signal design and control-relevant parameter estimation approach for highly interactive multivariate systems by Hyunjin Lee, Rivera, D.E.

“…A novel methodology that integrates a directional multisine input design procedure and control-relevant parameter estimation is developed in this paper,…”
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Control-relevant prefiltering: a systematic design approach and case study by Rivera, D.E., Pollard, I.F., Garcia, C.E.

“…The authors examine the use of control-relevant prefiltering applied to parameter estimation using prediction-error methods. The prefiltering step ensures that…”
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