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Process Optimization using High Throughput Automated Micro-Bioreactors in Chinese Hamster Ovary Cell Cultivation
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Economic-oriented stochastic optimization in advanced process control of chemical processes.

László Dobos1, András Király, János Abonyi

  • 1Department of Process Engineering, University of Pannonia, Egyetem Street 10, 8200 Veszprém, Hungary.

Thescientificworldjournal
|December 6, 2012
PubMed
Summary

This study introduces a multilevel stochastic optimization framework to find optimal chemical process setpoints. It minimizes constraint violations for improved economic performance while managing risk and uncertainty.

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Area of Science:

  • Chemical Engineering
  • Process Control
  • Optimization

Background:

  • Optimizing chemical processes is crucial for economic performance.
  • Optimal operating regions often approach constraints for product quality and safety.
  • Minimizing constraint violations is key to maximizing profit.

Purpose of the Study:

  • To develop a multilevel stochastic optimization framework.
  • To determine optimal setpoint values for control loops.
  • To manage risk levels, uncertainties, and costs associated with constraint violations.

Main Methods:

  • Direct search-type optimization.
  • Monte-Carlo simulation of the controlled process.
  • Application to benchmark problems including linear dynamical systems and nonlinear polymerization processes.

Main Results:

  • The framework effectively determines optimal setpoints under uncertainty.
  • It allows for predefined risk levels and violation costs.
  • Demonstrated success on both simple and complex chemical process models.

Conclusions:

  • The proposed framework enables robust process optimization.
  • It balances economic benefits with safety and quality constraints.
  • This approach is valuable for enhancing chemical process profitability and reliability.