Modeling and Simulation: Digital Twin

Descripció de Modelització i simulació: Bessó Digital

En l’Àrea de Modelització i simulació: Bessó Digital, som experts en realitzar estudis de viabilitat i/o millores de sistemes, mitjançant tècniques de modelització, simulació, optimització i bessons digitals en diferents àmbits de:

  • Logística del transport
  • Processos industrials i manufacturació
  • Salut i farmacèutic
 
Acompanyem a les empreses i institucions en el delicat procés de prendre decisions crítiques en el moment d’implementar nous processos i serveis a curt, mig o llarg termini.

Casos d’èxit de Modelització i simulació: Bessó Digital

Reduction of water consumption in production plants through the use of artificial intelligence and digital twins (Hydroless) for Friselva S.A. and bonÀrea

The company Friselva, together with the Alimentaria Guissona Corporation (bonÀrea) and with the participation of the inLab FIB from UPC as a technology center, is working on the Hydroless operational group project.

Artificial Intelligence-assisted police patrol manager for Mossos d’Esquadra

The inLab FIB, in collaboration with the Mossos d’Esquadra, has developed the proof of concept of an assistance tool for police response to everyday incidents based on artificial intelligence.

SORT (Sustainable Optimization of Route Transport) for the MICIU

Project to support the development of theoretical concepts and practical tools applied to optimized routes in the field of on-demand transportation.

Solution for the assignment of shifts on duty in the healthcare field for Lya2

Development of an algorithm for the assignment of shifts on duty of doctors in a hospital.

SDL-PAND

Generate a web application to analyze alternatives and define a work methodology that allows establishing a common framework for the different specialists.

Transport of students from the Barcelona Special Education Centers for the CEB

Developer of mathematical optimization algorithms to solve the corresponding problems of demand allocation and routing for heterogeneous fleets of vehicles.