GARCIA David

Research team

Engineering and Numerical Tools

Research themes

• Management and decision-making: planning, dynamic scheduling and piloting
• Human-system interactions (under development)

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Educational activities

• Disciplines : Innovation, Industrial system Engineering
• Pedagogy : Problem Based Learning
• Programs : Engineering school

Current research programs

• Dynamic scheduling of flexible job-shop manufacturing systems
• Affordance of production systems (under development)

PhD supervision

PhD programs in progress

SARAH OUARAB, “Characterization of affordances in a Cyber-Physical (Human) Production System, based on multimodal perception of human-system interactions”

Scientific animation

• In charge of research and innovation activities for CESI SUD-EST region
• Micro Learning Factory (MLF) platform project leader

Member of thesis committees

• Bayesian Network Structure Learning With Applications In Features Selection – Sergio Rodriguès de Morais, Université Claude Bernard Lyon 1 Laboratoire LIESP, 2009
• Simulation du refroidissement isochore d’un polymère semicristallin : prise en compte du diagramme PVT – Nadia Brahmia, Insa-Lyon, 2007
• Méthodes particulaires en vue de la simulation en plasturgie – Lucie Freret, Laboratoire Mathématiques Appliquées aux Systèmes, Ecole Central de Paris, 2007

Publications

Synthèse (2000-2023)

• ACL : 5
• INV : 0
• ACTI : 6
• ACTN : 0
• OS : 0
• Brevets : 1
• Articles de vulgarisation : 0

Selected publications

• Sow, M. C., Assila, A., Garcia, D., Martinez, S., Zghal, M., & Baudry, D. (2023). Towards the Development of a Digital Twin for Micro Learning Factory: A Proof of Concept. In Extended Reality (p. 284‑298). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-43401-3_19
• Madani Bezoui, Alexandru-Liviu Olteanu, Marc Sevaux, David Garcia. A new framework to solve flexible jobshop scheduling problems in the context of Industry 5.0. 32nd European Conference on Operational Research (EURO 32), Jul 2022, Espoo, Finland. ⟨hal-03718269⟩
• Slama, I., Ben-Ammar, O., Garcia, D., & Dolgui, A. (2022). Two-stage stochastic program for disassembly lot-sizing under random ordering lead time. In IFAC-PapersOnLine (Vol. 55, Issue 10, p. 1363‑1368). Elsevier BV. https://doi.org/10.1016/j.ifacol.2022.09.580
• Garcia, David & Tlahig, Houda & Bettayeb, Belgacem & Sahnoun, M’hammed. (2021). Evaluation of Dispatching Rules Performance for a DJSSP: Towards their Application in Industry 4.0. International Conference On Cyber Management And Engineering (CyMaEn), DOI: 10.1109/CyMaEn50288.2021.9497286.
• Garcia, David & Goff, Ronan & Gasse, Maxime & Aussem, Alexandre. (2014). Optimal Sensor Locations for Polymer Injection Molding Process. Key Engineering Materials. 611-612. 1724-1733. 10.4028/www.scientific.net/KEM.611-612.1724.
• Agazzi, A., Sobotka, V., Le Goff, R., Garcia, D., Jarny Y. A Methodology for the Design of Effective Cooling System in Injection Moulding. Int J Mater Form 3, 13–16 (2010). https://doi.org/10.1007/s12289-010-0695-2
• M’hamed BOUTAOUS, Patrick BOURGIN, Daniel HENG, David GARCIA, Optimization of radiant heating using the ray tracing method: Application to thermoforming, Journal of Advanced Science, 2005, Volume 17, Issue 1+2, Pages 139-145. https://doi.org/10.2978/jsas.17.139
• Guy Courbebaisse, David Garcia, Shape analysis and injection molding optimization,Computational Materials Science, Volume 25, Issue 4, 2002, https://doi.org/10.1016/S0927- 0256(02)00333-6.
• Guy Courbebaisse, David Garcia, Shape analysis and injection molding optimization, Computational Materials Science, Volume 25, Issue 4, 2002, https://doi.org/10.1016/S0927- 0256(02)00333-6.
• Michel Jourlin, Guy Courbebaisse, David Garcia, Polymer molding simulation – a mathematical imaging approach based on propagation of discrete distances, Computational Materials Science, 2000, https://doi.org/10.1016/S0927-0256(99)00096-8.