Food process models for training purpose through knowledge engineering methods - Université de Lille Accéder directement au contenu
Communication Dans Un Congrès Année : 2019

Food process models for training purpose through knowledge engineering methods

Ioana Suciu
  • Fonction : Auteur
Christophe Fernandez
  • Fonction : Auteur
Jason Sicard
Pascal Tournayre
Philippe Bohuon
Violaine Athès
D. Flick
  • Fonction : Auteur
Artemio Plana-Fattori
Cristian Trelea
  • Fonction : Auteur
Gilles Trystram
  • Fonction : Auteur
  • PersonId : 1203304
Sébastien Curet-Ploquin

Résumé

The use of models and simulators in food industry remains limited, despite its interest to predict complex situations, as shown by an abundant scientific literature . Although carried out in many establishments and universities, teaching about food modelling faces theoretical hurdles (mathematical formalism ...) who tend to discourage students, who are the future engineers and managers of food industries, but may have uncertain basis in physics, for instance. A generic response through a “learning by doing” approach is possible to teach these modelling approaches. Actually, digital resources offer an opportunity to address these issues . In the MESTRAL (Modelling and simulation for food processes) project, we have built such resources for teaching through knowledge representation and transfer tools, in particular electronic knowledge books (eK-Book). The eK-Book is a Web based tool, where knowledge is represented with concept maps, process and influence graphs, knowledge sheets, and their relationships stated as hypertext links. The effectiveness of knowledge transfer via these tools has already been validated . MESTRAL now encompasses 15 modules covering about 150h, each one presenting a couple (food, process) – from “heat exchanger for starch suspensions” to “cheese ripening” – in an eK-Book. Each module contains model-based simulators, used for virtual practice, and also includes exercises and tests for applying and assessing the knowledge acquired. MESTRAL has already been successfully tested for various classes, either for self-training or hybrid learning. Current prospects include its integration as a MOOC (Massive Open Online Courses). This work was supported by AgreenCamp project (ANR-15-IDFN-0001-01).
Fichier non déposé

Dates et versions

hal-03125592 , version 1 (29-01-2021)

Identifiants

  • HAL Id : hal-03125592 , version 1

Citer

Ioana Suciu, Amadou Ndiaye, Cédric Baudrit, Christophe Fernandez, Alain Marc Kondjoyan, et al.. Food process models for training purpose through knowledge engineering methods. ICEF13 - 13th International Congress on Engineering and Food, Sep 2019, Melbourne, Australia. ⟨hal-03125592⟩
225 Consultations
0 Téléchargements

Partager

Gmail Facebook X LinkedIn More