Resources

Sort by

Show as list




Toggle all information

Rhône-Alpes Champion: The Smart Mold

Project: BEinCPPS

Updated at: 29-09-2022

Show more information
Technologies and enablers
Information and communication technologies
Data collection, storage, analytics, processing and AI
Data acquisition
Comment: The data acquisition is performed by the monitoring core, performed in C. The BBB + Mikrobus + Thermoclicks provide access to the data gathered by the sensors. Sensors: -Temperature: MIKROELEKTRONIKA Thermocouple Type-K Glass Braid Insulated -Pressure: KISTLER 6190C
Data analytics
Comment: Historical analysis of the production process data, through data analysis, will enable to establish trends of the mold usage.
Data modelling
Comment: Usage of the UA-Modeler tool to model the OPC-UA address space, containing the variables describing the acquired data.
Human Machine Interfaces
Comment: Data visualization based on FIWARE Wirecloud widgets
Programming Frameworks – Software Development Kits (SDKs)
FIWARE
Smart Industry Context Information Management and Persistence
The Orion Context Broker Generic Enabler
Operating systems
Comment: The device platform supports a Linux distribution.
Data spaces
Programming Languages
Comment: The monitoring core has been developed in C. The OPC-UA layer has been developed in Node.js

Lombardy Champion - Zero-Hours Quality

Project: BEinCPPS

Updated at: 29-09-2022

Show more information
Technologies and enablers
Information and communication technologies
Data collection, storage, analytics, processing and AI
Comment: Cloud level: I2Lab
Data processing
Comment: Cloud level: Test Back-end
Data acquisition
Comment: Field level: Controller/Actuator (HW), TestExecutor (SW) Factory level: FIWARE IDAS Gateway for CPPS
Data analytics
Comment: The Field/Factory levels feed normalized streams of raw data to the Cloud level for further processing.
Data modelling
Comment: (offline): MSEE BIM Toolbox, UAModeler
Data storage
Comment: Cloud level: FIWARE Context Broker + Cygnus extension
Cognitive and artificial intelligence (AI) technologies - machine learning
Comment: Cloud level: I2Lab
Human Machine Interfaces
Comment: Factory level: Rule Editor (Android app), Test Front-End (Android app)
Programming Frameworks – Software Development Kits (SDKs)
FIWARE
Smart Industry Context Information Management and Persistence
The Cygnus Generic Enabler
Comment:

Cloud level: Cygnus extension

The Orion Context Broker Generic Enabler
Comment:

Cloud level

Pilot - Batteries

Project: DigiPrime

Updated at: 03-02-2022

Show more information
Technologies and enablers
Information and communication technologies
Data collection, storage, analytics, processing and AI
Data acquisition
Comment:

Operational services aim to collect product data on post-use Li-Ion batteries about their use phase in order to enable monitoring and full traceability of its life-cycle;

Data analytics
Comment:

Operational services aim to:

  • elaborate and analyse various data collected about post-use batteries to predict the conditions of the battery packs, modules and cells;
  • define a Decision Support System to identify the best disassembly and remanufacturing strategy, given the post-use Li-Ion battery conditions.
Data spaces
Digital manufacturing platforms - data platforms
Comment:

As the proactive exploitation of the DigiPrime platform enables the car-monitored SOH tracing and availability, less testing is needed to assess the residual capacity of the battery. Moreover, by knowing the structure of the battery packs, a decision support system can be implemented to adjust the de-and remanufacturing strategy accordingly and select the most proper cells for re-assembly second-life modules, thus unlocking a systematic circular value chain for Li-ion battery cells re-use. Furthermore, excessively degraded cells which cannot be re-used can be sent to high-value recycling, based on the knowledge of their material compositions.

Powered by Chris Decubber BV