Self-organized cascade collaborative optimization method for associated unit processes

Abstract

The process manufacturing industry includes multiple continuous unit processes, which cooperate with each other to complete a specific production task. Owing to the coupling between processes, it is often difficult to optimize a unit process to achieve global optimization. Considering the influence of the energy-mass coupling between the associated unit processes and the self-organized motion in the system on the process optimization operation, this study proposes a self-organized cascade collaborative optimization method for associated unit processes. By gradually producing a description of the operating status and coupling relationship of the system, a global optimization model can be constructed. First, reaction efficiency is proposed to evaluate the operating status of the system, and an online estimation model is constructed. Second, self-organized criticality is introduced to describe the evolution of the operating status in the collaborative production unit, and the mechanism knowledge and production data characteristics are combined to construct a coupling relationship model describing coupling and collaboration in the cascade system. Finally, a global optimization method for the system is constructed according to the coupling relationship between the associated unit processes and the cascading characteristic of the cascade system and within the unit process. The experimental results show that the method can realize global optimization of the cascade system, which improves the economic benefits compared with the existing production conditions and ensures stability of the system.