The research project Circular is offering a PhD thesis :
A collective intelligence approach for reuse-oriented decision support in circular design and remanufacturing at Grenoble Alpes University, LCIS laboratory.
"Circular Economy Creating circular industrial systems able to transform post-used products into new products require reuse-oriented strategies, resulting in component remanufacture that leads to the manufacture of totally new products from the transformation of post-used components [Brissaud and Zwolinski, 2017].
The reuse strategy is a manufacturing strategy driven by market conditions, both customer wishes and material procurements. The new product differs from previous products. Repurposed products are products that are built for a different purpose and belong to a different product family. Upgraded products are products of the initial family that get different functions and performances. Re-purposing and upgrading a product implies the interaction of multiple areas of expertise from all along the value chain to integrate the different constraints related to the product, the process and its resources, or the business model [Bauer et al., 2017]. In many cases, the customer also acts as a stakeholder.
Internet of Things and Multi-Agent Systems
In general, the Internet of Things (IoT) can be defined as : “A global network infrastructure, linking physical and virtual infrastructure, linking physical and virtual objects through the exploitation of data capture and communication capabilities. This infrastructure includes existing and evolving Internet and network developments. It will offer specific object-identification, sensor, actuator and connection capability as the basis for the development of independent federated services and applications. These will be characterized by a high degree of autonomous data capture, event transfer, network connectivity and interoperability [Moisescu et al., 2010]. IoT is a potential way of providing real-world entities with certain degree of “intelligence” so that the required level of context awareness can be achieved. Using IoT in manufacturing make then possible to consider the different systems involved in manufacturing as multi-agent systems. [Xing et al., 2011, Wang et al., 2016]
By using a social metaphor, the multi-agent paradigm offers a powerful framework for autonomous behaviors, social, organizational and cooperative exchanges needed for these kinds of artificial complex systems [Jamont and Occello, 2015]. Autonomy is one of the main concepts in the multi-agent issue : it is the ability of agents to control their actions and their internal states. Adaptation allows an agent to reason about the quality of its work according to constraints or incomplete data. The autonomy of agents implies no centralized control at a system level. An agent can be endowed with communication capabilities. Multi-agent systems aim to build collective intelligence systems. Nodes are not only autonomous but rather social entities. Agents are able to communicate, but also to interact adapting dynamically their interaction mode. The objective is not only to manage a system or to make a system adaptive but also to produce a collective emergent behavior [Wood and Galton, 2009].
Designing a Multi-Agent System (MAS) leads to find a way to build local agents structures and behaviors to drive the system of agents produces a particular global structure or a particular global functionality.
Further information about the thesis subject and criteria eligibility please download the file.