Multi-Parametric Optimization in Smart Manufacturing & Process Intensification

Abstract Smart Manufacturing and Process Intensification are major initiatives in the US and worldwide in which process systems engineering core areas, such as modelling, optimization, control and data analytics, play key role. In Smart manufacturing real-time optimization and on-line control based on big data analytics and modelling efforts constitute important challenges. In Process Intensification the in-silico modelling, synthesis and optimization of operable and safe process intensification alternatives constitutes a key research direction. Multi-parametric optimization provides a complete map of solutions of an optimization problem as a function of, unknown but bounded, parameters in the model, in a computationally efficient manner, without exhaustively enumerating the entire parameter space. In a Model-based Control framework, multi-parametric optimization can be used to obtain the governing ‘control laws’ – the optimal control/optimization variables as an explicit function of the state variables/parameters. This offers opportunities to (i) significantly accelerate and facilitate real-time/on-line optimization solution strategies - in the context of smart manufacturing applications, and (ii) effectively enable the systematic integration of operability criteria in the synthesis and optimization steps - in the context of process intensification. In this presentation, we will first provide a historical progress report of the key developments in multi-parametric optimization and control. We will then describe PAROC, a systematic framework and prototype software system which allows for the representation, modelling and solution of integrated design, operation and advanced control problems – with focus on sustainable energy systems, smart manufacturing and process intensification.