DOI: 10.5821/dissertation-2117-349568
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A contribution to chemical process operation support: new machine learning and surrogate models based approaches for process optimization, supervision and control

Ahmed Shokry Abdelaleem Taha Zied

Abstract: In the chemical process industry, the decision-making hierarchy is inherently model-based. The scale and complexity of the considered models (e.g., enterprise, plant or unit model) depend on the decision-making level (e.g., supply-chain management, planning, scheduling, operation) and the allowable time slot (weeks, hours, seconds) within which model simulation runs must be performed and their output is analyzed to support the decision making. The use of high-fidelity models, which include detailed physics-bas… Show more

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