Capex Opex Robust Optimization: a Software for Well-founded Economic Estimations and Process Optimization
Bozzini, Marcello
Prifti, Kristiano
Galeazzi, Andrea
Manenti, Flavio

How to Cite

Bozzini M., Prifti K., Galeazzi A., Manenti F., 2023, Capex Opex Robust Optimization: a Software for Well-founded Economic Estimations and Process Optimization, Chemical Engineering Transactions, 99, 619-624.


The preliminary stages of a project’s development and the early stages of the optimal design of a process often rely on an inaccurate and restricted amount of data. As the project goes through, the influence of design decisions on the project costs decreases and this creates an incentive to get the most precise cost information to guide the design at as early stage as possible. These are the concepts on which the Capex Opex Robust Optimization (CORO) is based on. CORO relies on a process simulation made in the commonly used commercial simulation package Aspen HYSYS to perform a rigorous economic evaluation of both CAPEX and OPEX. CORO allows to immediately get an initial economic evaluation and, most importantly, with a lower risk of human error. Microsoft Excel acts as GUI because of its broad applicability and user-friendly interface and it is well interconnected with the simulation package. In addition, CORO is able to execute a process’ optimization according to the degrees of freedom chosen by the user. The software is written in different programming languages; the macro for the data extraction from Aspen HYSYS’s simulation is written in Visual Basic for Application, while the economic evaluation and the optimization of the process are carried out by DLLs in C++ and Visual Basic.NET. An XML data sheet is used to carry the information from Microsoft Excel to the DLLs. In the long run, the data extraction from other simulation packages is expected to be implemented. This article exhibits the interconnection between the simulation package, Microsoft Excel and CORO and focuses on the mathematical tools implemented for the optimization of a process so far.