MUSIC | MUlti-layers control&cognitive System to drive metal and plastic production line for Injected Components

Summary

High Pressure Die Casting (HPDC) of light alloys and Plastic Injection Molding (PIM) are two of the most representative large-scale production-line in manufacturing field, which are strategic for the EU-industry largely dominated by SMEs. Due to the high number of process variables involved and to the non-sinchronisation of the process control units, HPDC and PIM are most "defect-generating" and "energy-consumption" processes in EU industry. In both, sustainability issue imposes that machines/systems are able to efficiently and ecologically support the production with higher quality, faster delivery times, and shorter times between successive generations of products.

The MUSIC project is strongly aimed at leading EU-HPDC/PIM factories to cost-based competitive advantage through the necessary transition to a demand-driven industry with lower waste generation, efficiency, robustness and minimum energy consumption. The development and integration of a completely new ICT tool, based on innovative Control and Cognitive system linked to real time monitoring, that allow an active control of quality, avoiding the presence of defects or over-cost by directly acting on the process-machine variables optimization or equipment boundary conditions.

The Intelligent Manufacturing approach will work at machine-mold project level to optimise/adapt the production of the specific product and can be extended at factory level to select/plan the appropriated production line. The sensors calibration and quality control of measurements will be the pre-requisite of Intelligent Sensor Network to monitor the real-time production and specific focus will be also devoted to Standardization issues.

The challenge of MUSIC is to transform a production-rate-dominated manufacturing field into a quality/efficiency-driven and integration-oriented one to exploit the enormous (and still underestimated) potential of HPDC/PIM through collaborative research and technological development, along the value chain.

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More information & hyperlinks
Web resources: http://music.eucoord.com/
https://cordis.europa.eu/project/id/314145
Start date: 01-09-2012
End date: 31-08-2016
Total budget - Public funding: 9 302 073,00 Euro - 6 135 000,00 Euro
Cordis data

Original description

High Pressure Die Casting (HPDC) of light alloys and Plastic Injection Molding (PIM) are two of the most representative large-scale production-line in manufacturing field, which are strategic for the EU-industry largely dominated by SMEs. Due to the high number of process variables involved and to the non-sinchronisation of the process control units, HPDC and PIM are most "defect-generating" and "energy-consumption" processes in EU industry. In both, sustainability issue imposes that machines/systems are able to efficiently and ecologically support the production with higher quality, faster delivery times, and shorter times between successive generations of products. The MUSIC is strongly aimed at leading EU-HPDC/PIM factories to cost-based competitive advantage through the necessary transition to a demand-driven industry with lower waste generation, efficiency, robustness and minimum energy consumption. The development and integration of a completely new ICT tool, based on innovative Control and Cognitive system linked to real time monitoring, that allow an active control of quality, avoiding the presence of defects or over-cost by directly acting on the process-machine variables optimization or equipment boundary conditions. The Intelligent Manufacturing approach will work at machine-mold project level to optimise/adapt the production of the specific product and can be extended at factory level to select/plan the appropriated production line. The sensors calibration and quality control of measurements will be the pre-requisite of Intelligent Sensor Network to monitor the real-time production and specific focus will be also devoted to Standardization issues. The challenge of MUSIC is to transform a production-rate-dominated manufacturing field into a quality/efficiency-driven and integration-oriented one to exploit the enormous (and still underestimated) potential of HPDC/PIM through collaborative research and technological development, along the value chain.

Status

CLO

Call topic

FoF-ICT-2011.7.1

Update Date

27-10-2022
Images
project_picturebig_1027-MUsic_intro.jpg
DDDT_platform_smartProdACTIVE.jpg
Geographical location(s)
Structured mapping
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Factories of the Future Partnership - Made in Europe Partnership

FP7 - Factories of the Future
FP7-FoF-2012
FoF-ICT-2011.7.1 - Smart Factories: Energy-aware, agile manufacturing and customisation
Significant innovations and achievements
Comment:

The data-driven digital twin in production line is a solution to measure, analyze and react oriented to zero defect manufacturing and to the maximization of the OEE improving the sustainability and profit of factory of future.

The application of Smart Prod ACTIVE system has been demonstrated and validated at foundry level. In the frame of HPDC production process, Operator and Process manager take advantage by adopting a centralized remote control system supporting process monitoring and quality prediction in real time. The decision is supported by cause-effect correlations, and proper reactions suggested by a continuously updated meta-model. Re-usability and flexibility of the Smart Prod ACTIVE system also allow agile re-start in case of small batches production

The same aproach is valid of any multi-stages production chain to produce part for all industrial sectors.

Significance of the results for SMEs
Comment:

The first successuful testing and applications are referred to SMEs

Lessons learned
Comment:

The challenge is the sensorization and data acquisition in the existing equipment not properly designed.

The data miming, real-time alerting and cognitive predictive meta-modelling is not a chimera.

Large-scale integrating project
Standards
Standards according to SDOs
OPC-UA
Comment:

OPC_UA has been intensively applied in the Data_driven Digital Twin of existing production line

Contribution of project to standardisation
Standardisation via European Standardisation Organisations
Comment:

Result of the MUSIC project  is a new starndard of Aluminium and aluminium alloys — Classification of Defects and Imperfections in High Pressure, Low Pressure and Gravity Die Cast Products, CEN, Brussels (2014).

Registered work item leading to EN (European Norm), TS (Technical Specification), TR (Technical Report)
Comment:

CEN T/R 16749: Aluminium and aluminium alloys — Classification of Defects and Imperfections in High Pressure, Low Pressure and Gravity Die Cast Products, CEN, Brussels (2014).

Autonomous Smart Factories Pathway
Comment:

Next future development and application is the automatic and intelligent retrofit excluding the current communication limits.

Dedicated software in silos
Data acquisition/monitoring/analysis (SCADA) implemented but isolated
Comment:

The data-driven digital twin is between SCADA and MOM

Connected IT and OT
MOM-SCADA systems connected
Comment:

The data-driven digital twin is between SCADA and MOM

Humans actively connected
Comment:

The GUI open the interaction with data-driven digital twin to data entry and KPI analytics

Realtime optimisation
Autonomous /online/realtime Manufacturing Process Optimisation on machine level
Comment:

The data-driven digital twin enables the real-time process optimization contorlling the process deviation affceting the quality and efficiency

Collaborative Product-Service Factories Pathway
Product, no Service
Use of CAD systems
Comment:

The data-driven digital twin uses CAD model of product and equipment

Environmental sustainability
Material efficiency
Waste minimisation
Comment: The development and integration of a completely new ICT tool, based on innovative Control and Cognitive system linked to real time monitoring, that allow an active control of quality, avoiding the presence of defects or over-cost by directly acting on the process-machine variables optimization or equipment boundary conditions. The C&CS application is for HPDC and PIM sectors that are the most “defect-generating” and “energy-consumption” processes in EU industry
Reduction of waste (in %)
20
Comment: the involved HPDC foundry is expecting for a 40% reduction in scrap rate
Circular economy
Co-evolution of products-processes-production systems (‘industrial symbiosis’)
Comment: The Intelligent Manufacturing approach will work at machine-mold project level to optimize/adapt the production of the specific product and can be extended at factory level to select/plan the appropriated production line
Reducing the consumption of energy
Reduction of energy consumption (in %)
10
Comment: energy consumption will be reduced by 5-10%, due to scrap reduction and more production efficiency
Information and communication technologies
Data spaces
Digital manufacturing platforms - data platforms
Advanced material processing technologies
Mechatronics and robotics technologies
Intelligent machinery components, actuators and end-effectors
Engineering tools
System modelling - digital twins, simulation
Cybersecurity
Cybersecurity Standards for digital manufacturing
De Facto industrial CyberSecurity standard developments
OPC-UA
Comment:

OPC_UA has been intensively applied in the Data_driven Digital Twin of existing production line

Interoperability (ICT)
General interoperability framework
Integration level interoperability
Connectivity & network interoperability – communication protocols
Semantic/information interoperability
OPC-UA
Comment:

OPC_UA has been intensively applied in the Data_driven Digital Twin of existing production line

Platform level interoperability
AAA - Access, Authorisation and Authentication
Application level interoperability
Open APIs and Communication Protocols
Industrial Reference ICT Architectures
Reference Architectural Model Industrie 4.0 (RAMI 4.0)
RAMI 4.0 Hierarchy Axis
Field Device
Comment:

The equipment and devices are sensorized to be deeper monitored

Work station
Comment:

Manufacturing cell is monitored with data acquisition from  any level.

Work centres - Production lines
Comment:

All stages of production line are connecteted to the Data-Driven Digital Twin platform

Enterprise - Factory
Comment:

All different production lines and plants can be monitored wiht the same platform because it is felxible and scalable.

Connected Enterprises - Factories
Comment:

Data-Driven Digital Twin enables the collaboration between OEM and Suppliers

Real-time communication capability
Manufacturing the products of the future
Resource efficient, sustainable products
Comment: The challenge of MUSIC is to transform a production-rate-dominated manufacturing field into a quality/efficiency-driven and integration-oriented one with lower waste generation, efficiency, robustness and minimum energy consumption.
Software development and ownership model
Proprietary software
Comment:

The Data-Driven Digita Twin Platform, Smart ProdACTIVE , is property of EnginSoft

Manufacturing system levels
Comment:

A fundamental innovative characteristic of digital twin platform, called Smart Prod ACTIVE, is the predictive Quality model integrating multi-resolution and multi-variate process data in a collaborative way to support the decision making process by Operator (Quality oriented), Production manager (Efficiency oriented - OEE) and Business manager (Cost-oriented)

Field Device
Comment:

The equipment and devices are sensorized to be deeper monitored

Work station
Comment:

Manufacturing cell is monitored with data acquisition from  any level.

Enterprise - Factory
Comment:

All different production lines and plants can be monitored wiht the same platform because it is felxible and scalable.

Connected Enterprises - Factories
Comment:

Data-Driven Digital Twin enables the collaboration between OEM and Suppliers

Connecting factories from different enterprises
Comment:

web-based platform and the access management is assential to collaborative platform sharing production data

Work centres - Production lines
Comment:

All stages of production line are connecteted to the Data-Driven Digital Twin platform

C22 Manufacture of rubber and plastic products
Result items:
automated production line for Plastic product
C24 Manufacture of basic metals
Result items:
steel equipment for hot working production line
C25 Manufacture of fabricated metal products, except machinery and equipment
Result items:
MiE_25-27_RP02: Excellent productive and flexible Manufacturing automation for open strategic autonomy
MiE_25-27_RP08: Quick response service deployment for maintaining optimal manufacturing operations using trusted AI and digital twins