BEinCPPS | Business Experiments in Cyber Physical Production Systems

Summary

BEinCPPS Innovation Action aims to integrate and experiment a CPS-oriented Future Internet-based machine-factory-cloud service platform firstly intensively in five selected Smart Specialization Strategy Vanguard regions (Lombardia in Italy, Euskadi in Spain, Baden Wuertemberg in Germany, Norte in Portugal, Rhone Alpes in France), afterwards extensively in all European regions, by involving local competence centers and manufacturing SMEs.

 

The final aim of this Innovation Action is to dramatically improve the adoption of CPPSs all over Europe by means of the creation, nurturing and flourishing of CPS-driven regional innovation ecosystems, made of competence centers, manufacturing enterprises and IT SMEs. The BE in CPPS project stems upon three distinct pillars:

  • A FI-based three-layered (machine-factory-cloud) open source platforms federation, integrated from state-of-the-art R&I advances in the fields of Internet of Things, Future Internet and CPS / Smart Systems and able to bi-directionally interoperate data pertaining to the machine, the factory and the cloud levels.
  • A pan-European SME-oriented experimentation ecosystem. In a first phase of the project, the five Champions will provide requirements to the platforms integrators. In a second phase, an Open Call for IT SMEs developers (applications experiments) will award 10 third parties. In a final third phase, the extended platform will be instantiated and deployed in additional 10 third parties equipment experiment SMEs.
  • A well-founded method and toolbox for Innovation management, where an existing TRL-based methodology for KETs technology transfer will be enriched by a CPPS certification, education and training programme for young talents and experienced blue collar workers and by a well-founded three-fold (objectives-variables-indicators) method for results assessment and evaluation.

 

More information & hyperlinks
Web resources: http://www.beincpps.eu/
https://cordis.europa.eu/project/rcn/198771/factsheet/en
Start date: 11-01-2015
End date: 31-10-2018
Total budget - Public funding: 9 517 643,00 Euro - 7 999 486,00 Euro
Cordis data

Original description

BEinCPPS Innovation Action aims to integrate and experiment a CPS-oriented Future Internet-based machine-factory-cloud service platform firstly intensively in five selected Smart Specialization Strategy Vanguard regions (Lombardia in Italy, Euskadi in Spain, Baden Wuertemberg in Germany, Norte in Portugal, Rhone Alpes in France), afterwards extensively in all European regions, by involving local competence centers and manufacturing SMEs. The final aim of this Innovation Action is to dramatically improve the adoption of CPPSs all over Europe by means of the creation, nurturing and flourishing of CPS-driven regional innovation ecosystems, made of competence centers, manufacturing enterprises and IT SMEs.
The BE in CPPS project stems upon three distinct pillars:
• A FI-based three-layered (machine-factory-cloud) open source platforms federation, integrated from state-of-the-art R&I advances in the fields of Internet of Things, Future Internet and CPS / Smart Systems and able to bi-directionally interoperate data pertaining to the machine, the factory and the cloud levels.
• A pan-European SME-oriented experimentation ecosystem. In a first phase of the project, the five Champions will provide requirements to the platforms integrators. In a second phase, an Open Call for IT SMEs developers (applications experiments) will award 10 third parties. In a final third phase, the extended platform will be instantiated and deployed in additional 10 third parties equipment experiment SMEs.
• A well-founded method and toolbox for Innovation management, where an existing TRL-based methodology for KETs technology transfer will be enriched by a CPPS certification, education and training programme for young talents and experienced blue collar workers and by a well-founded three-fold (objectives-variables-indicators) method for results assessment and evaluation.

Status

CLOSED

Call topic

FoF-09-2015

Update Date

27-10-2022
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Results:
The smart mold helps to improve the follow up of the production (QA). The plant operator will able to react more quickly to production deviations, therefore reducing strongly the scrap rates.
The main purpose of the system is to assess the average quality of the delivered product and to verify the correctness of the production process.
Results:

The smart mold provides Human Machine Interaction at several levels:

  • Production operators: real-time data and alerts, both at the work cell level, enterprise and cloud
  • Production managers and moldmakers: historical data analysis

The Rule Editor and the Test Front-End are Android apps allowing factory users to interact with the ZHQ system

Results:
OPC-UA for M2M communication, and NGSI for data publishing on the cloud
Results:
The experiment involves the "CPS-ization" of a mechanical piece of equipment used in the plastic injection process: the mold. It will be enabled with sensors to capture the physical properties relevant during the injection process, mainly temperature and pressure. In certain variations of the smart mold, it will also drive electrical actuators to perform in-mold mechanical movements, such as piece ejection or product version-switching. Sensors: -Temperature: MIKROELEKTRONIKA Thermocouple Type-K Glass Braid Insulated -Pressure: KISTLER 6190C Actuators: -Stepper motor: SM2863-5155
On the Field level is deployed Whirlpool-specific hardware (Controller and Actuator boards) and software (the Test Executor) that are directly connected to the Product under test.
Results:
The mold is mounted on top of an press machine, which performs the actual raw material conversion and performs the actual injection process. The smart mold communicates with the press to raise pre-configured alerts when the sensors detect abnormal situations, as well as to guide mechanical movements.
Online results of Product testing are also used for the early detection of problems in the manufacturing plant.
Results:
The smart mold publishes data to a production manager workstation, which in the context of a factory gathers all the data from all the work cells i.e. injection presses and provided an enterprise-level view of the deployed molds in production.
Offline analysis of historical Product testing results can be used to identify inefficiencies of production processes across the Enterprise.
Results:
The Smart Mold, as a true cyber-physical system, publishes data through a cloud infrastructure. In this cloud space, different applications are made available: -Visualization dashboards through widgets, to allow real-time visualization of production data -Data persistence: Store the physical data acquired by the sensors to enable historical analysis -Integration with information systems (ERP/MES): To trigger mainteinance operations for the mold when these are required
Results:
The plastic pieces as a result of the injection process.
The system is applied to whole Product items as they leave the assembly line.
Results:
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
Field level: Controller/Actuator (HW), TestExecutor (SW) Factory level: FIWARE IDAS Gateway for CPPS
Results:
Historical analysis of the production process data, through data analysis, will enable to establish trends of the mold usage.
The Field/Factory levels feed normalized streams of raw data to the Cloud level for further processing.
Results:
Usage of the UA-Modeler tool to model the OPC-UA address space, containing the variables describing the acquired data.
(offline): MSEE BIM Toolbox, UAModeler
Results:
Cloud level: FIWARE Context Broker + Cygnus extension
Results:
Data visualization based on FIWARE Wirecloud widgets
Factory level: Rule Editor (Android app), Test Front-End (Android app)
Results:
The device platform supports a Linux distribution.
Results:
The monitoring core has been developed in C. The OPC-UA layer has been developed in Node.js
Results:
All BEinCPPS components used in the Whirlpool demonstrator are open source software. Site-specific hardware components have been developed and are owned by Whirlpool. Solution-specific software components are proprietary software co-owned by the BEinCPPS partners involved in the demonstrator. All models and data is owned exclusively by Whirlpool.
Results:
The experiment involves the "CPS-ization" of a mechanical piece of equipment used in the plastic injection process: the mold. It will be enabled with sensors to capture the physical properties relevant during the injection process, mainly temperature and pressure. In certain variations of the smart mold, it will also drive electrical actuators to perform in-mold mechanical movements, such as piece ejection or product version-switching. Sensors: -Temperature: MIKROELEKTRONIKA Thermocouple Type-K Glass Braid Insulated -Pressure: KISTLER 6190C Actuators: -Stepper motor: SM2863-5155
On the Field level is deployed Whirlpool-specific hardware (Controller and Actuator boards) and software (the Test Executor) that are directly connected to the Product under test.
Results:
The mold is mounted on top of an press machine, which performs the actual raw material conversion and performs the actual injection process. The smart mold communicates with the press to raise pre-configured alerts when the sensors detect abnormal situations, as well as to guide mechanical movements.
Online results of Product testing are also used for the early detection of problems in the manufacturing plant.
Results:
The smart mold publishes data to a production manager workstation, which in the context of a factory gathers all the data from all the work cells i.e. injection presses and provided an enterprise-level view of the deployed molds in production.
Offline analysis of historical Product testing results can be used to identify inefficiencies of production processes across the Enterprise.
Results:
The Smart Mold, as a true cyber-physical system, publishes data through a cloud infrastructure. In this cloud space, different applications are made available: -Visualization dashboards through widgets, to allow real-time visualization of production data -Data persistence: Store the physical data acquired by the sensors to enable historical analysis -Integration with information systems (ERP/MES): To trigger mainteinance operations for the mold when these are required