AIChE Journal Highlight: Integrating Process Design, Scheduling, and Model Predictive Control | AIChE

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AIChE Journal Highlight: Integrating Process Design, Scheduling, and Model Predictive Control

October
2020

Decision-making in the chemical process industries (CPI) at multiple timescales is a cornerstone in the discipline of chemical engineering. Chemical engineers have developed systematic approaches and tools for these decisions in batch processing, including long-term process design optimization and shorter-term dynamic decisions (e.g., production scheduling and control practices). These systematic approaches use different models and techniques that require different sets of skills and expertise. As a result, real-time and offline process decisions are usually not driven by a single source but by multiple sources, which can hinder operations and reduce the profitability of a process.

In the AIChE Journal article “Integrated Process Design, Scheduling, and Model Predictive Control of Batch Processes with Closed-Loop Implementation,” authors Baris Burnak and Efstratios Pistikopoulos (Texas A&M Univ.) address the challenges of multiscale decisions by proposing a unified theory and modeling framework to integrate process design, production scheduling, and advanced control problems for batch processes in a single dynamic optimization formulation.

Burnak and Pistikopoulos introduce...

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