The synthesis of different isocyanates is a highly energy-intensive and complex process; hence, there is a lot of scope and potential for developing technologies and formulations for sustainable development. However, optimizing the production process requires a model validated with measurement data and describes the real system with sufficient accuracy to achieve significant time and cost savings while improving product quality. Models can support the manufacturing process quickly and accurately, increase the selectivity of products to meet market needs, reduce byproducts and energy consumption, and improve the fluidity of setting key performance indicators (KPIs) to the expected value. Methylenedianiline (MDA) is an intermediate product of the synthesis of methylene diphenyl diisocyanate (MDI), which is formed by a condensation reaction between aniline and formaldehyde in an acidic environment. The conditions of the condensation reaction essentially determine the quantitative and qualitative properties of the final MDI product mixture. The development of a model describing the formation of MDA is therefore considered a critical step. The results show that by increasing the complexity of the model and defining new components and reactions, a better model can be achieved describing the reaction system.
Limitations regarding process design, optimization, and control often occur when using particular process simulators. With the implementation of connection methodologies, integrated tools could be made by coupling popular process simulation software with each other or with programming environments. In the current paper, we summarized and categorized the existing research regarding the application of multi-software engineering in the chemical industry, with an emphasis on software connections. CAPE-OPEN, COM, OPC, and native integration were discussed in detail, with the intention to serve as a guide for choosing the most suitable software combination and connection. These hybrid systems can handle complex user-defined problems and can be used for decision support, performing custom unit operations, operator training, process optimization, building control systems, and developing digital twins. In this work, we proposed the use of process simulator Aspen HYSYS linked together with the numeric computing platform MATLAB to solve a reaction kinetic parameter identification problem regarding the production of 𝛾-valerolactone.