A NOVEL FLEXIBILITY ANALYSIS APPROACH FOR PROCESSES WITH STOCHASTIC PARAMETERS

This paper presents a novel flexibility analysis approach for process systems with stochastic parameters. Assuming a linear model for the process and a Gaussian distribution model for the parameter uncertainty, a computational strategy is proposed which fully exploits the probabilistic structure of the problem, and with which a stochastic flexibility index can be determined. This index measures the probability that a given design is feasible to operate by explicitly taking into account the existence of operating degrees of freedom. A major feature of the suggested procedure is that it can handle any number of correlated and/or independent parameters. Examples are presented to illustrate the proposed methodology. © 1990.