Optimising Circular Supply Chains with AI and Data-Driven Decision Making
As manufacturing ecosystems become increasingly interconnected, managing complex supply chains requires more than traditional planning tools. Companies must be able to evaluate multiple production scenarios, coordinate suppliers, and optimise logistics while considering sustainability objectives. Within the CIRCULOOS project, this challenge is addressed through the development of SCOPT (Supply Chain OPTimisation), an AI-driven tool designed to support smarter, data-based decision-making in circular manufacturing supply chains.
SCOPT applies advanced AI planning and optimisation techniques to analyse manufacturing workflows and supply chain configurations. By modelling factories, resources, and production processes as interconnected systems, the tool can determine the most efficient sequence of actions required to produce a product while minimising costs, emissions, and resource consumption. The optimisation process considers both intra-factory logistics, such as machine operations and material flows, and inter-factory supply chain arrangements across multiple partners.
A key feature of SCOPT is its ability to evaluate alternative production scenarios. For example, the system can compare manufacturing processes that use non-recycled materials versus those that use recycled materials, calculating the environmental impact of each option. In one scenario presented in the deliverables, the optimisation model identifies different production paths and quantifies their CO₂ emissions, demonstrating how circular production strategies can significantly reduce environmental impact.
The tool operates within the broader CIRCULOOS digital ecosystem, integrating with several platform components. Data from the Supply Chain Digital Twin (SCDT) provides models of factories and supply chains, while sustainability indicators from the GRETA lifecycle assessment tool supply environmental metrics such as CO₂ emissions. Using these inputs, SCOPT computes optimal production sequences and supply chain configurations that balance operational efficiency with sustainability objectives.
Beyond individual factories, the optimisation framework can also analyse multi-factory supply chains, identifying how materials, recycled resources, and products should flow between partners. For example, waste materials generated by one factory can be redirected to another facility, where they are transformed into recycled inputs, creating a more circular, resource-efficient manufacturing network.
By combining AI planning algorithms, lifecycle sustainability data, and digital twin simulations, the SCOPT tool provides manufacturers with a powerful decision-support system. It enables companies to explore different supply chain scenarios, optimise production processes, and design collaborative manufacturing networks that are both efficient and environmentally sustainable.