Robust Operability Analysis of Industrial Processes with Parameter Uncertainties

Abstract

Robust operability is one of the key properties of industrial processes with uncertain parameters, which helps the designers assess the operating performance and improve production reliability quite early. The objective of this work is to develop a framework of operability analysis to depict the robust operational space and quantificationally assess the robust operability of the plant. First, a derivative-free optimization-based flexibility analysis model is designed to identify the largest flexibility space. Then, a line projection method is adopted to locate the boundary points of the operational space. Finally, the Delaunay triangulation and convex hull theory are combined to identify the robust operational space; meanwhile, the optimal operating condition is found, which provides operators with straightforward guidance to ensure reliable operations. After calculating the space volume, the ratio to the physical operational space can assess robust operability. Three case studies are considered to show the efficiency of the proposed method.