SusChEM: An integrated framework for process design, control and scheduling [PAROC]

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This research project aims for an innovative shift in addressing three common tasks performed by process engineers: design, scheduling, and control of process systems. These tasks are typically performed independently of each other, without taking into consideration the interactions and trade-offs amongst them. The development and use of novel strategies, procedures, and tools for decision making for process system engineering has the potential, as part of smart manufacturing and process improvement efforts, to contribute significantly to a sustainable future. The primary aim of this research project is to provide a useful conceptual framework and software tool for the integration of design, control and scheduling tasks. The framework and software platform is being applied to the optimization of a residential combined cooling, heating and power generation network system. The project findings are being incorporated into graduate courses at Texas A&M University. The developed tool is being deployed as an open access software tool for the benefit of the academic and industrial communities. The integration of process design, control and scheduling remains an open grand challenge in process systems engineering. While significant research efforts have been made in the last twenty years to sequentially integrate design with control, and more recently control with scheduling, a generally accepted methodology to unify the field is still lacking. The multi-scale framework being developed features (1) a high-fidelity dynamic model representation, also involving global sensitivity analysis, parameter estimation and mixed integer dynamic optimization capabilities; (2) a suite/toolbox of model approximation methods; (3) a host of multi-parametric programming solvers for mixed continuous/integer problems; (4) a state-space modeling representation capability for scheduling and control problems; and (5) an advanced toolkit for multi-parametric/explicit Model Predictive Control and moving horizon reactive scheduling problems. The intellectual merit of the activity lies in the integration of the three tasks (design, control and scheduling) within a unified multiscale framework and in the ability to acquire optimal operation policies, optimal model based controllers and optimal designs of process systems through a single optimization formulation. Additionally, there is merit in the capability to close the loop with a cross validation of the outcomes with the original model, ensuring optimal and stable operation.