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PROBLEMATIC
- How to supervise and control a soft/hard system partially observable in time and/or space?
- How to reschedule production organisation in a decentralised system?
COMPETENCIES
- CPS Network to enlarge information system functional coverage
- Emerging decision to increase reactivity and productivity in a production system
- Reactive system
- Physical inspiration system
- Biological inspiration system - Emergence measurement
- Functional analysis
- Non-functional analysis
APPLICATIONS
- QC
- 100% control
- Quantification of quality
- Security
- Monitoring and prediction
- Control
PUBLICATIONS
Toward CPS-agent based quality control platform for industry 4.0 Narjes Alaya, Baudouin Dafflon, Nejib Moalla, Yacine Ouzrout, 2017
Using Physics Inspired Wave Agents in a Virtual Environment: Longitudinal Distance Control in Robots Platoon M. Gueriau, B Dafflon, F Gechter International Journal of Monitoring and Surveillance Technologies Research
Agent based monitoring for smart cities: Application to traffic lights R Elchamaa, B Dafflon, Y Ouzrout, F Gechter Software, Knowledge, Information Management & Applications (SKIMA), 2016
A cyber-physical model for platoon system M El-Zaher, B Dafflon, F Gechter Software, Knowledge, Information Management and Applications (SKIMA), 2015
LINKS
- CPS for traffic regulation (liban)
- CPS for manufacture (vfos)
PROBLEMATIC
- How to Integrate MES with other information systems (PLM, ERP, external traceability system)?
- How to accelerate the MES deployment with a Model-Based System Engineering approach?
- How to get value out of MES data with new MES parametric functions (diagnosis, prognosis)?
COMPETENCIES
- Model-Based System Engineering (MBSE) to model manufacturing systems, MES and link between them
- Information System interoperability to integrate MES with other information systems (PLM, ERP, external traceability system)
- Knowledge on standard (IS95, EPCIS, etc) to develop generic and parametric approaches
- Artificial Intelligence tools for data analysis to get value out of MES data
APPLICATIONS
- Identification of Overall Equipment Effectiveness (OEE) evolution for all root causes (equipment, human, recipe, scheduling, material) based on MES data
- Diagnosis of product quality default based on unitary traceability and process historian
- Proposal architecture for integration between PLM-ERP and MES
- Modelling of MES function interactions with manufacturing system based on engineering system approach
PUBLICATIONS
L. Pietrac, A. Leleve, S. Henry, “On the use of SysML for Manufacturing Execution System design”, IEEE International Conference on Emerging Technologies and Factory Automation (ETFA'11), Toulouse, France, 5-9 September 2011
A. Ben Khedher, S. Henry and A. Bouras, “Quality improvement of product data exchanged between engineering and production through the integration of dedicated information system”, ASME 2012 11th Biennial Conference On Engineering Systems Design And Analysis (ESDA2012) , Nantes, France, July 2012
T. M. L. Diallo, S. Henry, Y. Ouzrout. Using Unitary Traceability for an Optimal Product Recall. IFIP International Conference on Advances in Production Management Systems (APMS’14), Ajaccio, France, 20-21 Sept 2014. 438: 159-166. http://dx.doi.org/10.1007/978-3-662-44739-0_20
N. H. Tran, S. Henry, and E. Zamaï, Generic and configurable diagnosis function based on production data stored in Manufacturing Execution System, Third European Conference of the PHM Society - PHME16, Bilbao, Spain, 5-8 July 2016.
A. Ben Khedher, S. Henry and A. Bouras, “Integration between MES and Product Lifecycle Management”, IEEE International Conference on Emerging Technologies and Factory Automation (ETFA'11), Toulouse, France, 5-9 September, 2011
LINKS
- Projet FUI Traçaverre, Thèse Thierno DIALLO
- Thèse NGUYEN Hoang, région Auvergne Rhône-Alpes
- Thèse Anis BEN KHEDDER
PROBLEMATIC
- How can a system make an "intelligent" decision or help a decision-maker to make a decision that is consistent with his or her environment?
- How to model and formalize complex decision-making processes?
COMPETENCIES
- Multi-Agent models for complex systems FOR Multi-Agents models for complex decision-making processes
- Context-aware simulation models for decision making FOR Distributed simulation models for decision support
- Decision-making processes & Collective Intelligence FOR Distributed behavioural models for the emergence of collective decisions
- Cognitive-behaviours modelling & negotiation/collaboration protocols FOR Agent behaviour models and collaborative protocols for decision-making support
APPLICATIONS
- EU FP7 Project Easy-IMP: MAS for Smart Product Development
- PHC Lebanon : MAS for decision making in Smart Cities
- MAS Simulation for decision making in collaborative Supply Chains
- SCIADO Company: Agent models for adaptative learning in production & logistic context
PUBLICATIONS
[Lopez-Morales & al., 2015] “MKMSIS: A Multi-Agent Knowledge Management System for Industrial Sustainability”
[Elchamaa, 2017] “A Local Leader election protocol applied to decentralized traffic regulation”
[Alaya, 2017] “Toward Agent-CPS based collaborative platform for industry 4.0.”
[Liu & al., 2014] Multi-criteria Decision Making based on Trust and Reputation in Supply Chain
LINKS
- EU FP7 Project Easy-IMP
- PHC Lebanon
- Supply Chain Simulation
- SCIADO Company
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