Integrating production scheduling and process control using latent variable dynamic models

doi:10.1016/j.conengprac.2019.104201

This content will become publicly available on November 11, 2020

Title: Integrating production scheduling and process control using latent variable dynamic models

Full Record
Other Related Research

Authors:: Tsay, Calvin; Baldea, Michael

Publication Date:: 2020-01-01

Sponsoring Org.:: USDOE

OSTI Identifier:: 1573872

Grant/Contract Number:: OE0000841

Resource Type:: Publisher's Accepted Manuscript

Journal Name:: Control Engineering Practice

Additional Journal Information:: Journal Name: Control Engineering Practice Journal Volume: 94 Journal Issue: C; Journal ID: ISSN 0967-0661

Publisher:: Elsevier

Country of Publication:: United Kingdom

Language:: English

Citation Formats


                    Tsay, Calvin, and Baldea, Michael. Integrating production scheduling and process control using latent variable dynamic models.  United Kingdom: N. p., 2020. 
        Web.  doi:10.1016/j.conengprac.2019.104201.

Copy to clipboard


                    Tsay, Calvin, & Baldea, Michael. Integrating production scheduling and process control using latent variable dynamic models.  United Kingdom.  doi:10.1016/j.conengprac.2019.104201.

Copy to clipboard


                    Tsay, Calvin, and Baldea, Michael. Wed .  
        "Integrating production scheduling and process control using latent variable dynamic models".  United Kingdom.  doi:10.1016/j.conengprac.2019.104201.

Copy to clipboard


                    
@article{osti_1573872,

  title        = {Integrating production scheduling and process control using latent variable dynamic models},

  author       = {Tsay, Calvin and Baldea, Michael},

  abstractNote = {},

  doi          = {10.1016/j.conengprac.2019.104201},

  journal      = {Control Engineering Practice},

  number       = C,

  volume       = 94,

  place        = {United Kingdom},

  year         = {2020},

  month        = {1}

}

Copy to clipboard

Journal Article:

Free Publicly Available Full Text

This content will become publicly available on November 11, 2020

Publisher's Version of Record

DOI: 10.1016/j.conengprac.2019.104201

Other availability

Search WorldCat to find libraries that may hold this journal

Save / Share:

Export Metadata

Save to My Library

Similar records in OSTI.GOV collections:

Production scheduling and operational control: New algorithms with applications to the mining industry

Miscellaneous Tan, S.

In this thesis, several aspects of production scheduling and operational control problems have been investigated. The scope of the study has included (a) analysis of current issues, (b) development of related theory, mathematical modeling, and solution algorithms, (c) implementation, validation, and application demonstration of the models developed in this research. A new algorithm integrating the dynamic programming and branch-and-bound techniques, called the RBDP algorithm, has been developed for solving multi-stage optimization problems and modeling the resource-constrained scheduling problem. A logical linear programming model (LLP) has also been developed which incorporates logical constraints of the form, [open quotes]IF [a[sub 1] x[submore »« less
Emergent Subpopulation Behavior Uncovered with a Community Dynamic Metabolic Model of Escherichia coli Diauxic Growth

Journal Article Succurro, Antonella ; Segrè, Daniel ; Ebenhöh, Oliver ; ... - mSystems

ABSTRACT Microbes have adapted to greatly variable environments in order to survive both short-term perturbations and permanent changes. A classical and yet still actively studied example of adaptation to dynamic environments is the diauxic shift of Escherichia coli , in which cells grow on glucose until its exhaustion and then transition to using previously secreted acetate. Here we tested different hypotheses concerning the nature of this transition by using dynamic metabolic modeling. To reach this goal, we developed an open source modeling framework integrating dynamic models (ordinary differential equation systems) with structural models (metabolic networks) which can take into accountmore »« less
Cited by 2
DOI: 10.1128/mSystems.00230-18
Constructing Dynamic Event Trees from Markov Models

Journal Article Paolo Bucci ; Jason Kirschenbaum ; Tunc Aldemir ; ... - Proceedings of the Eighth International Conference on Probabilistic Safety Assessment and Management

In the probabilistic risk assessment (PRA) of process plants, Markov models can be used to model accurately the complex dynamic interactions between plant physical process variables (e.g., temperature, pressure, etc.) and the instrumentation and control system that monitors and manages the process. One limitation of this approach that has prevented its use in nuclear power plant PRAs is the difficulty of integrating the results of a Markov analysis into an existing PRA. In this paper, we explore a new approach to the generation of failure scenarios and their compilation into dynamic event trees from a Markov model of the system.more »« less
Integrated model for production planning and scheduling in underground coal mining

Thesis/Dissertation Gillenwater, E.L.

This research develops a series of models that complements the production planning process in underground coal mining. Two LP models that address the aggregate planning process and two-machine scheduling model are developed. The first model, the mine production scheduling model, is a straight-forward LP formulation. Monthly production and inventory levels are determined. The objective is to minimize the monthly production and inventory holding costs of the schedule. The second model, the sectional production scheduling model, is also an LP application. This model incorporates a quality-blending requirement into the determination of the weekly sectional production and inventory levels. The third modelmore »« less
Wind-To-Hydrogen Energy Pilot Project

Technical Report Ron Rebenitsch ; Randall Bush ; Allen Boushee ; ...

WIND-TO-HYDROGEN ENERGY PILOT PROJECT: BASIN ELECTRIC POWER COOPERATIVE In an effort to address the hurdles of wind-generated electricity (specifically wind's intermittency and transmission capacity limitations) and support development of electrolysis technology, Basin Electric Power Cooperative (BEPC) conducted a research project involving a wind-to-hydrogen system. Through this effort, BEPC, with the support of the Energy & Environmental Research Center at the University of North Dakota, evaluated the feasibility of dynamically scheduling wind energy to power an electrolysis-based hydrogen production system. The goal of this project was to research the application of hydrogen production from wind energy, allowing for continued wind energymore »« less
DOI: 10.2172/951588

Full Text Available

Similar Records