Rhône-Alpes Champion: The Smart Mold

Rhône-Alpes Champion: The Smart Mold
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Structured mapping
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Demonstrator (project outcome type)
Industrial pilot or use case
C MANUFACTURING
C22 Manufacture of rubber and plastic products
C28 Manufacture of machinery and equipment n.e.c.
Economic sustainability
Product quality - Quality assurance
Comment: 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.
Environmental sustainability
Reducing the consumption of energy
Social sustainability
Increasing human achievements in manufacturing systems
Comment:

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
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
Cybersecurity
Cybersecurity Standards for digital manufacturing
De Facto industrial CyberSecurity standard developments
OPC-UA
Interoperability (ICT)
Comment: OPC-UA for M2M communication, and NGSI for data publishing on the cloud
General interoperability framework
Integration level interoperability
Semantic/information interoperability
Comment: All the information is stored in a single context in the Orion Context Broker.
OPC-UA
Industrial Reference ICT Architectures
Reference Architectural Model Industrie 4.0 (RAMI 4.0)
RAMI 4.0 Hierarchy Axis
Field Device
Comment: 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
Work station
Comment: 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.
Enterprise - Factory
Comment: 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.
Connected Enterprises - Factories
Comment: 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
Product
Comment: The plastic pieces as a result of the injection process.
Business models
Business model aspects of digital platform deployment
Autonomous Smart Factories Pathway
Off-line optimisation
Off-line Digital Manufacturing Process Optimisation on machine level
Collaborative Product-Service Factories Pathway
Product-Service Innovation
Closed loop PSS Design (Connected to users data)
Standards
Comment: OPC-UA, NGSI, RAMI 4.0, EUROMAP Engineering: SysML, BPMN
Standards according to SDOs
OPC-UA
Manufacturing system levels
Field Device
Comment: 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
Work station
Comment: 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.
Enterprise - Factory
Comment: 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.
Connected Enterprises - Factories
Comment: 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