Abstract
As a founder of the Process Systems Engineering (PSE) discipline, Professor Roger W.H. Sargent had set ambitious goals for a systematic new generation of a process design paradigm based on optimization techniques with the consideration of future uncertainties and operational decisions. In this paper, we present a historical perspective on the milestones in model-based design optimization techniques and the developed tools to solve the resulting complex problems. We examine the progress spanning more than five decades, from the early flexibility analysis and optimal process design under uncertainty to more recent developments on the simultaneous consideration of process design, scheduling, and control. This formidable target towards the grand unification poses unique challenges due to multiple time scales and conflicting objectives. Here, we review the recent progress and propose future research directions.
Highlights
It has been over half a century since Professor Roger W.H
With the advent of computers, he further emphasized the opportunity to expand the process design problem to account for foreseeable variations in the plant environment over its life cycle to achieve more reliable and robust operations. “(During the process design phase) Many parameters are left available for adjustment during plant operation, such as flow rates, tank levels, operating pressures, etc., but here the design places limits on the range of variation possible.” stated Professor Sargent to underpin the interdependence between the design and the uncertainty of future operational decisions
The Process Systems Engineering (PSE) community has been accumulating formidable knowledge and know-how on mathematical modeling techniques in the fields of process design and operations, and developed efficient tools to solve these advanced models since Professor Sargent had outlined the future of PSE in his 1967 perspective article [1]
Summary
It has been over half a century since Professor Roger W.H. Sargent envisioned a paradigm shift in chemical process design methodologies, from ad hoc engineering judgment for specific problems to fully computerized systematic approaches based on complex mathematical models [1]. The goal is to model tractable dynamic design optimization problems that account for the scheduling and control decisions to guarantee the operability and even profitability of the operation under all foreseeable conditions.
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