The recycling chain is viewed as a collaborative ecosystem of heterogeneous and evolving entities. The definition and development of information systems is a recurring theme at the intersection of computer science and industrial engineering. Collaborative information systems aim to facilitate data sharing and the orchestration of processes among multiple partners, relying on services provided by various stakeholders involved in the collaboration. To address the need for agile configuration, model-driven and service-oriented architectures have been developed. A persistent challenge in this domain is ensuring the required interoperability among the various information systems.
The supervisory team has experience in the definition and management of collaborative information systems across diverse contexts requiring agile coordination among stakeholders: biomass valorisation (Houngbé et al., 2019), deduction of collaborative processes (Montarnal et al., 2018), Industry 4.0/5.0, and the enhancement of decision-making processes through new technologies (Rosin et al., 2022).
Scientific Challenges
Several gaps have been identified that will be studied during this PhD:
- Integrating agility on several levels: chain reconfiguration, partner changes, decision process changes, late flows adaptation to materials variability,
- Meta-modelling of minimal necessary information needs based on the required levels of collaboration, to ensure both process lifecycle management and situational awareness.
- Assessing data quality and strategies to address data gaps (e.g., data augmentation, synthetic data creation),
- Monitoring a data-driven model of the value chain that can trigger alerts and enable the reconfiguration of the recycling chain as needed,
- Identifying the technologies most suited to support the information system features.
- Defining a set of methods and tools that are generic enough to be applied to various recycling chains and support the required reconfigurations.