Projects overview
AI REGIO | Regions and DIHs alliance for AI-driven digital transformation of European Manufacturing SMEs
01-10-2020
-30-09-2023
DigiPrime | Digital Platform for Circular Economy in Cross-sectorial Sustainable Value Networks
01-01-2020
-31-12-2023
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;
QU4LITY | Digital Reality in Zero Defect Manufacturing
01-01-2019
-31-07-2022
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)
Z-BRE4K | Strategies and Predictive Maintenance models wrapped around physical systems for Zero-unexpected-Breakdowns and increased operating life of Factories
01-10-2017
-31-03-2021
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.
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.
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.
UPTIME | UNIFIED PREDICTIVE MAINTENANCE SYSTEM
01-09-2017
-31-08-2020
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.
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.
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.
PreCoM | Predictive Cognitive Maintenance Decision Support System
01-11-2017
-31-10-2020
SERENA | VerSatilE plug-and-play platform enabling remote pREdictive mainteNAnce
01-10-2017
-30-09-2020
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.
FALCON | Feedback mechanisms Across the Lifecycle for Customer-driven Optimization of iNnovative product-service design
01-01-2015
-01-01-2018
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.
OPTIMAL | Automated Maskless Laser Lithography Platform for First Time Right Mixed Scale Patterning
01-10-2022
-30-09-2026
COMPOSITION | Ecosystem for Collaborative Manufacturing Processes _ Intra- and Interfactory Integration and Automation
01-09-2016
-31-08-2019
CREMA | Cloud-based Rapid Elastic MAnufacturing
01-01-2015
-01-01-2018
vf-OS | Virtual Factory Open Operating System
01-10-2016
-30-09-2019
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.
BEinCPPS | Business Experiments in Cyber Physical Production Systems
11-01-2015
-31-10-2018
INCLUSIVE | Smart and adaptive interfaces for INCLUSIVE work environment
01-10-2016
-30-09-2019
ZAero | Zero-defect manufacturing of composite parts in the aerospace industry
01-10-2016
-30-09-2019
ICP4Life | An Integrated Collaborative Platform for Managing the Product-Service Engineering Lifecycle
01-01-2015
-01-01-2019
SAFIRE | Cloud-based Situational Analysis for Factories providing Real-time Reconfiguration Services
01-10-2016
-30-09-2019
ENCOMPASS | ENgineering COMPASS
01-10-2016
-30-09-2019
TWIN-CONTROL | Twin-model based virtual manufacturing for machine tool-process simulation and control
10-01-2015
-30-09-2018
IMPROVE | Innovative Modeling Approaches for Production Systems to raise validatable efficiency
09-01-2015
-31-08-2018
ambliFibre | adaptive model-based Control for laser-assisted Fibre-reinforced tape winding
01-09-2015
-31-08-2018
FACTS4WORKERS | Worker-Centric Workplaces in Smart Factories
01-12-2014
-01-12-2018
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.
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.
5G-Ensure | 5G Enablers for Network and System Security and Resilience
01-11-2015
-31-10-2017
Cyper Physical Production System and digital twins requires data collection from real system
USE-IT-WISELY | Innovative continuous upgrades of high investment product-services
01-09-2013
-30-11-2016
3D laser scanning techniques