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FALCON | Feedback mechanisms Across the Lifecycle for Customer-driven Optimization of iNnovative product-service design

01-01-2015

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31-12-2017

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

FALCON aims to gather Product Usage Information from Product Embedded Information Devices as well as customer feedback through the internet and social media. These information will be re-used directly to improve product-services. These product-service optimizations are carried out in a multidisciplinary way by stakeholders from different domains. FALCON further supports the process of product-service optimization by providing a collaboration platform.

BEinCPPS | Business Experiments in Cyber Physical Production Systems

11-01-2015

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31-10-2018

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Technologies and enablers
Information and communication technologies
Data collection, storage, analytics, processing and AI
Result items:
Lombardy Champion - Zero-Hours Quality
Lombardy Champion - Zero-Hours Quality
Cloud level: I2Lab
Data acquisition
Result items:
Lombardy Champion - Zero-Hours Quality
Lombardy Champion - Zero-Hours Quality
Field level: Controller/Actuator (HW), TestExecutor (SW) Factory level: FIWARE IDAS Gateway for CPPS
Rhône-Alpes Champion: The Smart Mold
Rhône-Alpes Champion: The Smart Mold
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

IMPROVE | Innovative Modeling Approaches for Production Systems to raise validatable efficiency

09-01-2015

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31-08-2018

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Technologies and enablers
Information and communication technologies
Comment: ICT solutions enable the work in IMPROVE. Big Data is collected from the production plants and modern machine learning techniques are used to learn models from data, drastically reducing the manual modelling efforts. Learned models can adapt to the modern, fast changing systems and are available for tasks like condition monitoring and root cause analysis. The results are then displayed to the user, hiding the systems complexity.
Data collection, storage, analytics, processing and AI
Result items:
An algorithm to identifying the root cause of a fault
An algorithm to identifying the root cause of a fault
Data acquisition

QU4LITY | Digital Reality in Zero Defect Manufacturing

01-01-2019

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31-07-2022

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Technologies and enablers
Information and communication technologies
Result items:
D2.11 Reference Architecture and Blueprints (Version 1)
D2.11 Reference Architecture and Blueprints (Version 1)
Data collection, storage, analytics, processing and AI
Result items:
D2.11 Reference Architecture and Blueprints (Version 1)
D2.11 Reference Architecture and Blueprints (Version 1)
Pilot - SIEMENS SIMATIC Products Quality Improvements
Pilot - SIEMENS SIMATIC Products Quality Improvements
Data acquisition
Result items:
D2.11 Reference Architecture and Blueprints (Version 1)
D2.11 Reference Architecture and Blueprints (Version 1)
Pilot - SIEMENS SIMATIC Products Quality Improvements
Pilot - SIEMENS SIMATIC Products Quality Improvements

Through innovative algorithms and statistical methods, possible data sources for predictive quality control can be identified and evaluated. Moreover, by cooperation of all project partners, the realization of data access and acquisition along the whole process chain can be realized. With a focus on algorithms and methodology, a use case-specific algorithm is going to be implemented and validated to maintain high prediction accuracy.

Data availability is a challenge: Limited access to measurement data (due to limited access to third-party systems)

AI REGIO | Regions and DIHs alliance for AI-driven digital transformation of European Manufacturing SMEs

01-10-2020

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30-09-2023

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Technologies and enablers
Information and communication technologies
Data collection, storage, analytics, processing and AI
Result items:
AI-enhanced control strategy for production environment
AI-enhanced control strategy for production environment
Automatic Capability Matchmaking For Re-Configurable Robotics Platform
Automatic Capability Matchmaking For Re-Configurable Robotics Platform
Idss For Predictive Quality Assurance
Idss For Predictive Quality Assurance
Intelligent Computer Vision for Digital Twin and Reinforcement Learning for Assembly Line Balancing
Intelligent Computer Vision for Digital Twin and Reinforcement Learning for Assembly Line Balancing
Water leakage detection
Water leakage detection
Data acquisition
Result items:
Natural Language Processing for Troubleshooting
Natural Language Processing for Troubleshooting

UPTIME | UNIFIED PREDICTIVE MAINTENANCE SYSTEM

01-09-2017

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28-02-2021

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Technologies and enablers
Information and communication technologies
Comment:

UPTIME will reframe predictive maintenance strategy in a systematic and unified way with the aim to fully exploit the advancements in ICT and maintenance management by examining the potential of big data in an e-maintenance infrastructure taking into account the Gartner’s four levels of data analytics maturity and the
proactive computing principles.

Data collection, storage, analytics, processing and AI
Comment:

UPTIME will enable manufacturing companies to reach Gartner's four levels of data analytics maturity for optimised decision making - each one building on the previous one: Monitor, Diagnose and Control, Manage, Optimize - aims to optimise in-service efficiency and contribute to increased accident mitigation capability by avoiding crucial breakdowns with significant consequences. UPTIME Components UPTIME_DETECT & UPTIME_PREDICT and UPTIME_ANALYZE aim to enhance the methodology framework for data processing and analytics. The key role for the UPTIME_DETECT and UPTIME_PREDICT components are data scientists who are in charge of developing, testing and deploying algorithmic calculations on data streams. In this way, the component is able to to identify the current condition of technical equipment and to give predictions. On the other hand, the UPTIME_ANALYZE is a data analytics engine driven by the need to leverage manufacturers’ legacy data and operational data related to maintenance, and to extract and correlate relevant knowledge.

Data acquisition
Comment:

The UPTIME_SENSE component is responsible for the acquisition of sensor data from the field. It is utilised to enable previously disconnected assets, to communication with the UPTIME Cloud.

Z-BRE4K | Strategies and Predictive Maintenance models wrapped around physical systems for Zero-unexpected-Breakdowns and increased operating life of Factories

01-10-2017

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31-03-2021

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Technologies and enablers
Information and communication technologies
Comment:

The Z-Break solution uses a variety of communication protocols. HTTP, OPC-UA, IEEE 802.15.4e and IEC WirelessHART. The Hypertext Transfer Protocol (HTTP) is an application protocol for distributed, collaborative, hypermedia information systems. HTTP is the foundation of data communication for the World Wide Web. OPC UA supports two protocols. The binary protocol is opc.tcp://Server and http://Server is for Web Service. Otherwise OPC UA works completely transparent to the API. IEEE 802.15.4 is a technical standard which defines the operation of low-rate wireless personal area networks (LR-WPANs). It specifies the physical layer and media access control for LR-WPANs, and is maintained by the IEEE 802.15 working group, which defined the standard in 2003. WirelessHART is a wireless sensor networking technology based on the Highway Addressable Remote Transducer Protocol (HART). Developed as a multi-vendor, interoperable wireless standard, WirelessHART was defined for the requirements of process field device networks. Also, it uses the NGSI protocol. NGSI is a protocol developed to manage Context Information. It provides operations like managing the context information about context entities, for example the lifetime and quality of information and access (query, subscribe/notify) to the available context Information about context Entities.

Data collection, storage, analytics, processing and AI
Comment:

Z-BRE4K solution provides a big data analytics framework for the identification of the deterioration trends to extended towards prescriptive maintenance. Advanced data analysis tools are under development, to be applied to the quality and production data to realise zero-defect and zero-break down production. Furthermore, it involves models for anomaly detection, that are capable of identifying the machine states where the operation deviated from the norm.  This is achieved by collecting the data from the machine sensors in chunks of time and processing them in batch through deep learning models. The models are trying to recreate their inputs, and this results in an observable measure called Reconstruction Error, which is used to identify states that the models aren’t capable of addressing sufficiently (which constitutes an anomaly.

Data acquisition
Comment:

The suggestion beyond the state-of-the-art is to have intelligent machine simulators so an information and knowledge rich platform can provide an accurate account of the machine’s current state and provide predictive (look ahead) potential scenarios of future time type, severity and risks of breakdown. Collected, processed, integrated and aggregated data will be structured and fed in real-time into networked simulators enabling advanced analysis and visualization to provide smart services, higher fidelity and prediction accuracy for production and manufacturing assets management. Different schemes for data collection configuration are implemented (ranging dedicated IoT devices with independent methodologies) to collect raw data from sensors, pre-process and aggregate the information, and share the results with other services through an IDS connector. The Z-Bre4k IDS connectors have a reference architecture to ensure data sovereignty and integrity throughout this collection phase.

vf-OS | Virtual Factory Open Operating System

01-10-2016

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31-10-2019

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Technologies and enablers
Information and communication technologies
Comment:

From a technological point of view, Open vf-OS Platform will provide elements covering the connected world, allowing the exchange and collaboration of information between companies on a value stream thanks to the cloud approach to be adopted (vf-Platform). The Open vf-OS covers from the control device level, where information from the systems (IoT, CPS, embedded systems) is gathered, processed and empowered.

Data collection, storage, analytics, processing and AI
Data acquisition
Result items:
vfOS - ID5.1a - Data Infrastructure Middleware(M18)
vfOS - ID5.1a - Data Infrastructure Middleware(M18)

SAFIRE | Cloud-based Situational Analysis for Factories providing Real-time Reconfiguration Services

01-10-2016

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30-09-2019

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Technologies and enablers
Information and communication technologies
Data collection, storage, analytics, processing and AI
Comment: Methodology for reconfiguration and optimisation of products and factories based on predictive big-data analytics. Emphasizing security, privacy & trust based on situational awareness. The methodology will address technical and organizational issues for extension and introduction of tools/services for re-configuration and optimisation of factories / products.
Result items:
SAFIRE Electrolux pilot: Cloud-driven product optimization
SAFIRE Electrolux pilot: Cloud-driven product optimization
SAFIRE OAS pilot: Optimisation of production processes and preventive maintenance activities
SAFIRE OAS pilot: Optimisation of production processes and preventive maintenance activities
SAFIRE ONA pilot: Adaptive Machining
SAFIRE ONA pilot: Adaptive Machining
Data acquisition
Result items:
SAFIRE Electrolux pilot: Cloud-driven product optimization
SAFIRE Electrolux pilot: Cloud-driven product optimization
SAFIRE OAS pilot: Optimisation of production processes and preventive maintenance activities
SAFIRE OAS pilot: Optimisation of production processes and preventive maintenance activities
SAFIRE ONA pilot: Adaptive Machining
SAFIRE ONA pilot: Adaptive Machining

SERENA | VerSatilE plug-and-play platform enabling remote pREdictive mainteNAnce

01-10-2017

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31-03-2021

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

Digital models enahnced with real world data acquired from sensor devices will be used as the basis of physical phenomena that affect the operational condition of the equipment, such as degradation. THis will result in the improvement of the accuracy of the predictive maintenance functionalities of the SERENA platfrom and tools.

DAT4.ZERO | Data Reliability and Digitally-enhanced Quality Management for Zero Defect Manufacturing in Smart Factories and Ecosystems

01-10-2020

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31-03-2024

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Technologies and enablers
Information and communication technologies
Result items:
Digital Quality Analytics Solution for extrusion processes using machine learning and human-oriented dashboards
Digital Quality Analytics Solution for extrusion processes using machine learning and human-oriented dashboards
Data collection, storage, analytics, processing and AI
Result items:
Digital Quality Analytics Solution for extrusion processes using machine learning and human-oriented dashboards
Digital Quality Analytics Solution for extrusion processes using machine learning and human-oriented dashboards
Digitally-enhanced monitoring system
Digitally-enhanced monitoring system
Data acquisition
Result items:
Digital Quality Analytics Solution for extrusion processes using machine learning and human-oriented dashboards
Digital Quality Analytics Solution for extrusion processes using machine learning and human-oriented dashboards

VIEWS | Validation and Integration of Manufacturing Enablers for Future Wing Structures

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Technologies and enablers
Information and communication technologies
Data collection, storage, analytics, processing and AI
Result items:
Metrology-integrated Robotics
Metrology-integrated Robotics
Data acquisition
Result items:
Metrology-integrated Robotics
Metrology-integrated Robotics

RFID Positioning System – Use of multiple RFID receivers within the cell would allow for 3D location tracking of the parts to be assembled in the system, ensuring parts are correctly present and in the right locations before proceeding.

 

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