In this work, we present an optimisation-based decision support framework developed within the PROPLANET project, aimed at assisting potential users of the PROPLANET Replication Tool in the design and assessment of sustainable by design (SSBD) coatings production processes.

According to the information obtained with simple box for planet (SB4P) two multiobjective optimisation models have been formulated to simultaneously maximise coating production volume and minimise pollutant emissions generated along the production chain across different environmental media, including air, water, and soil. The model explicitly accounts for the final performance and quality properties of the coatings, ensuring that sustainability improvements are achieved without compromising functional requirements.

To approximate the Pareto front of the formulated problem, multiobjective metaheuristic optimisation techniques have been applied, specifically the Non-dominated Sorting Genetic Algorithm II (NSGA-II). The resulting set of solutions provides decision-makers with a structured overview of feasible compromises, enabling informed choices depending on production goals and environmental constraints.

The proposed approach demonstrates how multiobjective optimisation and simulation-based methods can effectively support decision-making in the development of sustainable industrial coatings, highlighting the potential of evolutionary optimisation tools to accelerate the transition towards environmentally responsible manufacturing processes.