Advanced Integration Methods for the Efficient Symbiosis of Process Networks – AIMS

Abstract

The AIMS project proposal addresses the challenges associated to the "efficient use of resources and raw materials" and to the use of "clean, efficient and safe energy systems" in the Process Industries from a holistic, non-hierarchical and cross-sectoral point of view. Departing from the limitations imposed by the conservation and transfer laws, AIMS will rely on the Process Systems Engineering (PSE) approach to propose efficient ways to intensify the interactions between different processing systems and supply chains, identifying and promoting Industrial Symbiosis opportunities, and fostering collaborative decision-making and circular economy solutions. The proposal is aimed at overcoming the limitations of the current ad-hoc Industrial Symbiosis approaches, based on identifying opportunities through expert analysis. These strategies, even after a systematic local search, usually lead to sub-optimal solutions. On the contrary, the solutions to be proposed through AIMS will be based on the systematic collection and processing of data, the use of common models ensuring interoperability between information and knowledge management tools, and the transparent assessment of solutions. Thus, AIMS will develop models, methods and tools able to identify efficient resource processing and transformation networks under three working paradigms: Unified approach: development of holistic tools to harmonize concerns and constraints (economic, environmental and social) from the different stakeholders involved; Multi-scale view: integration of operational, tactical and strategic decision-making levels within a global, unified and consistent information model; Multi-sectoral applicability: Adaptability to open systems, independent from specific industrial sectors or scenarios, and from the geographic or macroeconomic context. The models to be developed shall be able to consider two basic aspects of the problem, often over-simplified or even ignored: the existence of multiple, conflicting, non-additive objectives, and the uncertainty associated to the lack of reliable information, not always revealed by the competing counterparts. In order to formulate and solve the resulting models, multi-objective optimization approaches will be complemented with decomposition strategies, methods based on game theories, and metaheuristics. Extensive use of model reduction techniques and sensitivity analysis methods is expected to discard noise, seize relevant factors for decision making and finally improve the efficiency of the required optimization strategies. The systematic methods and tools to be developed will be validated on a diverse set of cases, both from academia and industry, at large and reduced scale. Case studies will involve process industries and networks (chemical, petrochemical, oil & gas, agro-food, etc.), for which simultaneous management of shared resources will be addressed taking into account economic, environmental and social concerns, in accordance with the EU Responsible Research & Innovation policy. Applications in renewable energy, water treatment, etc. and circular economy initiatives led by organizations from the third sector will be also addressed, demonstrating AIMS potential to identify alternatives promoting the efficient use of resources, and further validating the generality of the approach and the specific procedures developed.