ABSTRACT During the design of chemical processes some design specifications (e.g. safety, environmental and performance) must be met. The satisfaction of these design specifications is complicated by the presence of uncertainty in (a) the empirically derived mathematical models, and (b) fluctuations in the process conditions. Therefore, for a chemical process (CP) to operate reliably, it must be able to tolerate these uncertainties. A CP that has this attribute is said to be flexible. More rigorously, the flexibility property of a CP is its ability to readily adjust to uncertainties in order to meet design specifications. In order to account for uncertainties, rule-of-thumb based over-design factors have typically been used. These rules-of-thumb often lead to sub-optimal operation of the chemical process. To address this, in our research, we have been developing systematic strategies for calculating optimal over-design factors. In this research review paper, we give a comparative analysis of current methods for estimating chemical process flexibility, and the subsequent use of such measures in the optimization of chemical processes under uncertainty. Specifically, we consider methods based on the branch-and-bound and split-and-bound strategies. Current methods require satisfaction of some convexity (or concavity) conditions, which are difficult to verify for practical problems. To address the latter, we have developed algorithms, which bring minimal requirements of convexity (or concavity) to the problem.
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