Ph. D. Project
Title:
System-of-Systems Design and Modelling of a Multi-Level Recycling Value Chain
Dates:
2025/10/15 - 2028/10/14
Supervisor(s):
Other supervisor(s):
Pr Trentesaux Damien (damien.trentesaux@uphf.fr)
, Dr Daquin Cecilia (cecilia.daquin@uphf.fr)
Description:
Recycling value chains in France and Europe face significant challenges due to the diversity of actors involved, the fragmentation of management systems, the heterogeneity of material flows, and increasing economic and regulatory constraints. This structural complexity is further amplified by the interdependence of processes, variability in available resources, and the growing need for industrial and technological sovereignty. While the literature on the circular economy is extensive, much of the existing research remains focused on local process optimization (e.g., energy efficiency, waste reduction, yield improvement) or on individual actors, without fully addressing the systemic dynamics and multi-scale interactions required to build robust and resilient recycling networks.
To address these challenges, recent studies emphasize the need to move beyond siloed approaches and develop systemic models capable of integrating the entire product life cycle, delayed decision feedback, sector-specific constraints, and multi-level governance mechanisms. These approaches must consider not only the physical and economic characteristics of materials but also the collaborative dynamics between heterogeneous actors, the uncertainty of material flows, market unpredictability, and the rapid evolution of technologies and regulations.
The objective of this PhD is to design and model the recycling value chain as a true System of Systems (SoS), explicitly addressing the complexity arising from the multiplicity and diversity of stakeholders, their interactions at various levels (local, regional, national), and their potentially divergent goals. The developed architecture will aim to enhance the agility, flexibility, and overall resilience of the network while ensuring its robustness and long-term viability in the face of regulatory, economic, and technological changes.
Coherently with the objective, the following scientific contributions are expected. The first scientific contribution will focus on designing a multi-level architecture that enables the coherent integration of local initiatives such as industrial symbiosis (micro level) with regional and national recycling strategies (meso and macro levels). The modelling approach will rely on the foundational principles of Systems of Systems engineering,
including the explicit definition of actors' capabilities in order to clearly structure their roles, responsibilities, and interactions within the ecosystem.
The second contribution is the formalization of generic and adaptable modelling patterns to represent dynamic interactions between actors, product flows, and regeneration processes. These patterns will facilitate reuse, generalization, and adaptation of the models to different industrial contexts, thereby reducing the time required to design or reconfigure the network.
Moreover, given the fast evolution of technologies, regulatory frameworks, market conditions, and the possible emergence of new recycling actors, a structural adaptability and dynamic reconfiguration mechanisms must be incorporated. These capabilities are essential to ensure the architecture remains responsive and does not become rigid or obsolete. An agent-based modelling approach is then particularly suited to capture such dynamics and can be adopted for implementation and validation.
Particular attention will also be paid to the articulation between the different decision-making levels (strategic, tactical, operational) and the modelling of multi-actor decision processes. This approach will enable a better understanding of the complexity of governance and management mechanisms within recycling value chains, while supporting the precise definition of required data, its update frequency, and its aggregation level.
To address these challenges, recent studies emphasize the need to move beyond siloed approaches and develop systemic models capable of integrating the entire product life cycle, delayed decision feedback, sector-specific constraints, and multi-level governance mechanisms. These approaches must consider not only the physical and economic characteristics of materials but also the collaborative dynamics between heterogeneous actors, the uncertainty of material flows, market unpredictability, and the rapid evolution of technologies and regulations.
The objective of this PhD is to design and model the recycling value chain as a true System of Systems (SoS), explicitly addressing the complexity arising from the multiplicity and diversity of stakeholders, their interactions at various levels (local, regional, national), and their potentially divergent goals. The developed architecture will aim to enhance the agility, flexibility, and overall resilience of the network while ensuring its robustness and long-term viability in the face of regulatory, economic, and technological changes.
Coherently with the objective, the following scientific contributions are expected. The first scientific contribution will focus on designing a multi-level architecture that enables the coherent integration of local initiatives such as industrial symbiosis (micro level) with regional and national recycling strategies (meso and macro levels). The modelling approach will rely on the foundational principles of Systems of Systems engineering,
including the explicit definition of actors' capabilities in order to clearly structure their roles, responsibilities, and interactions within the ecosystem.
The second contribution is the formalization of generic and adaptable modelling patterns to represent dynamic interactions between actors, product flows, and regeneration processes. These patterns will facilitate reuse, generalization, and adaptation of the models to different industrial contexts, thereby reducing the time required to design or reconfigure the network.
Moreover, given the fast evolution of technologies, regulatory frameworks, market conditions, and the possible emergence of new recycling actors, a structural adaptability and dynamic reconfiguration mechanisms must be incorporated. These capabilities are essential to ensure the architecture remains responsive and does not become rigid or obsolete. An agent-based modelling approach is then particularly suited to capture such dynamics and can be adopted for implementation and validation.
Particular attention will also be paid to the articulation between the different decision-making levels (strategic, tactical, operational) and the modelling of multi-actor decision processes. This approach will enable a better understanding of the complexity of governance and management mechanisms within recycling value chains, while supporting the precise definition of required data, its update frequency, and its aggregation level.
Conditions:
Desired Profile:
Technical skills: Background in systems engineering, modelling and simulation (preferably multi-agent systems), familiarity with Systems of Systems concepts, and interest in circular economy. Experience with tools like AnyLogic or SysML is recommended.
Professional skills: Autonomy, strong English proficiency, motivation for research in sustainable development, and ability to work in interdisciplinary environments.
Application Materials: CV, cover letter, summary of Master's research work, transcripts, and any other documents supporting your motivation for this PhD.
Technical skills: Background in systems engineering, modelling and simulation (preferably multi-agent systems), familiarity with Systems of Systems concepts, and interest in circular economy. Experience with tools like AnyLogic or SysML is recommended.
Professional skills: Autonomy, strong English proficiency, motivation for research in sustainable development, and ability to work in interdisciplinary environments.
Application Materials: CV, cover letter, summary of Master's research work, transcripts, and any other documents supporting your motivation for this PhD.
Department(s):
| Modelling and Control of Industrial Systems |
Funds:
ANR - Projet PEPR RegeNexus