Research database

Specific industrial needs address include: •Leveraging the research and results developed by previous research projects in this field•Scalability and portability of the developed model for potential application in other FCA plants, through the digitalization of the built heritage.•Optimization of the Body Shop’s energy consumption the improvement of the model predictive control•Visualization of the status of current infrastructure using Virtual and Augmented Reality (VAR) for predictive maintenance, driving towards the factory of the future and Industry 4.0•Development of a Digital Twin Factory prototype based on the interaction between BIM/BEM models and IoT devices integrated system•Identification of metering and actuators to be installed in the plant in order to apply the model predictive control in the real environment •Development of a Digital Twin for test bed of AI alghortims and for Facility Management (Scientific Challenge)•Development and test of a model predictive control (Scientific Challenge)•Integration of energy consumption in the model predictive control (Scientific Challenge)•Identification of additional meters and actuators installation in the body shop area (Technical Challenge)•Integration among BIM/IoT as standard for the FCA Real Estate oriented to OpenBIM (Technical challenge)•Use of VAR for Facility Management of Digital Twin Factory using BIM (Scientific Challenge)