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Description This saying captures the trade-off between resources, production time, quality and performance that are inherent in every manufacturing process.
 An Autonomous Illumination System for Vehicle Documentation Based on Deep Reinforcement Learning Result title An Autonomous Illumination System for Vehicle Documentation Based on Deep Reinforcement Learning
 Periodic Reporting for period 1 - OPTIMAI (Optimizing Manufacturing Processes through Artificial Intelligence and Virtualization) Result description The advent of Industry 4.0 has certainly increased productivity and efficiency in manufacturing.
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Description more energy efficient, improve manufacturing productivity, optimize raw material consumption, flexible mold changes and manufacturing capability of producing multiple components,...etc.
Comments efficient, sustainable products Manufacturing future products Manufacturing the products of the future Improved energy eficciency by 20% Domain 1 - Advanced Manufacturing Processes Impact Workshop D1
 Domain 1: Advanced manufacturing processes Taxon title Domain 1: Advanced manufacturing processes
 RP 1.6 Material efficient Manufacturing processes Taxon description Increasing the material efficiency can be developed at different levels of manufacturing system through: (i) Process modification, (ii) On site recovery and reuse of waste materials and (iii) Transformation
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Comments Manufacturing the products of the future Manufacturing future products Methodologies for the (re-)design of Product-Service Systems and their support services.
 (KER G5)Service solution for Condition Based Maintenance (CBM) of Robot Cells Result description A new data logger HW/SW solution has been developed for gathering data from virtually any device or system. This is the main component for the new Condition based Maintenance (CbM) solution.
 C MANUFACTURING Taxon title C MANUFACTURING
 Measurement, sensing, condition and performance monitoring technologies Taxon description Continuous monitoring of the condition and performance of the manufacturing system on component and machine level, enables sustainable and competive manufacturing, also by introducing autonomous diagnosis
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Description and activities: Supporting a common and structured understanding of key enablers and cross-cutting factors with regard to the deployment of digital technologies, including digital platforms, for manufacturing
Organisation THE MANUFACTURING TECHNOLOGY CENTRE LIMITED LBG
 Video - Digital platforms for Manufacturing - a Step Stone towards Data Spaces for Manufacturing Result title Video - Digital platforms for Manufacturing - a Step Stone towards Data Spaces for Manufacturing
 Video - Data Space Pathway Result description The Data Space pathway is composed of 5 levels, characterised by increasing maturity degrees of the manufacturing company / industrial case towards a full exploitation of Data Economy in Manufacturing.
 Video - introduction and use cases - Circular Economy and Manufacturing Result acronym Video-CE-Manufacturing
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Description Using a modular approach the PRACE system can even be recombined to use only parts of the robot system for dedicated applications, i.e. using only a single arm or using the system without mobility.
Comments Manufacturing the products of the future Manufacturing future products Customised products Manufacturing future products Manufacturing the products of the future Economic sustainability Manufacturing
 Demonstrator PRACE (Automatica 2014) Result description by the worker) - Assembly task is formulated on a semantic level - Automatic code transformation using a database with assembly skills - Closed loop testing of workflow in simulation or real robot system
 C MANUFACTURING Taxon title C MANUFACTURING
 Domain 2: Adaptive and smart manufacturing systems Taxon description The set of research priorities under this domain focuses on innovative manufacturing equipment at component and system level, including mechatronics, control and monitoring systems The research priorities
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Description Currently, RLW systems are limited in their applicability due to an acute lack of systematic ICT-based simulation methodologies to navigate their efficient application in automotive manufacturing processes
Comments Material efficient Manufacturing processes FoF Partnership SRIA Research priorities Sub-Domain 1.2 Complex structures, geometries and scale Domain 1: Advanced manufacturing processes Domain 3: Digital
 Domain 1: Advanced manufacturing processes Taxon title Domain 1: Advanced manufacturing processes
 RP 1.6 Material efficient Manufacturing processes Taxon description Increasing the material efficiency can be developed at different levels of manufacturing system through: (i) Process modification, (ii) On site recovery and reuse of waste materials and (iii) Transformation
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Description The DAPhNE project brings together three manufacturing sectors (ceramic, glass and cement) with common problems in relation to the energy consumption of their firing processes, seeking common solutions
Comments Manufacturing the products of the future Manufacturing future products Resource efficient, sustainable products Manufacturing future products Manufacturing the products of the future Economic sustainability
 Domain 1: Advanced manufacturing processes Taxon title Domain 1: Advanced manufacturing processes
 RP 1.6 Material efficient Manufacturing processes Taxon description Increasing the material efficiency can be developed at different levels of manufacturing system through: (i) Process modification, (ii) On site recovery and reuse of waste materials and (iii) Transformation
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Comments Economic sustainability Manufacturing performance characteristics Circular economy Manufacturing performance characteristics Environmental sustainability Environmental sustainability Manufacturing
 KASEM platform and Knowledge Model for Machine-Tool Result description In parallel, a knowledge model has been developed within the knowledge-based system of KASEM.
 C MANUFACTURING Taxon title C MANUFACTURING
 Measurement, sensing, condition and performance monitoring technologies Taxon description Continuous monitoring of the condition and performance of the manufacturing system on component and machine level, enables sustainable and competive manufacturing, also by introducing autonomous diagnosis
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Description The objectives of the “Socially sustainable manufacturing for the Factories of the Future” – SO SMART are to: • Develop a socially sustainable ecosystem assessment framework, including guidelines to
Comments SRIA Research priorities RP 5.1 New manufacturing education methods and e-learning FoF Partnership SRIA Research priorities Domain 5: Human-centric manufacturing RP 5.3 Levels of automation and continuous
 Final Report Summary - SO SMART (Socially sustainable manufacturing for the Factories of the Future – SO SMART) Result title Final Report Summary - SO SMART (Socially sustainable manufacturing for the Factories of the Future – SO SMART)
 RP 5.3 Levels of automation and continuous adaptation of workplaces Taxon title RP 5.3 Levels of automation and continuous adaptation of workplaces
 RP 5.1 New manufacturing education methods and e-learning Taxon description System interoperability and standardised interfaces are required to integrate e-learning tools with real life manufacturing processes and systems in the backend.
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Description Digital Product Passports and a Circular Economy Decision Support System will be developed as high-level tools, facilitating the trustful exchange of assets, the selection of optimum circular stock management
 Circular business models for EU manufacturing value chains Result title Circular business models for EU manufacturing value chains Result description D12 Circular business models for EU manufacturing value chains Report on potential business models for manufacturing based on circularity principles R PU M9 TNO
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Description The aim of FaBiMed proposal is to improve and develop new manufacturing techniques, based on micromoulding, specific for biomedical microdevices.
Comments Business models and strategies for disruptive manufacturing processes Domain 1: Advanced manufacturing processes Domain 2: Adaptive and smart manufacturing systems FoF Partnership SRIA Research priorities
 C MANUFACTURING Taxon title C MANUFACTURING
 RP 1.6 Material efficient Manufacturing processes Taxon description Increasing the material efficiency can be developed at different levels of manufacturing system through: (i) Process modification, (ii) On site recovery and reuse of waste materials and (iii) Transformation
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Description DENiM identifies skills gaps and develops training to build competences to support energy sustainability in smart manufacturing processes through the seamless integration of digital technologies, education
 Design of a Lifecycle-Oriented Environmental and Economic Indicators Framework for the Mechanical Manufacturing Industry Result title Design of a Lifecycle-Oriented Environmental and Economic Indicators Framework for the Mechanical Manufacturing Industry
 Current Best Practices, Stakeholder Analysis and Pilot Scenarios for Energy Efficient Manufacturing Systems Result description Present status quo with respect to best practices for energy efficient manufacturing systems along with a stakeholder analysis and pilot scenarios
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Description The ENERMAN digital twin will predict the economic cost of the consumed energy based on the collected and predicted Energy Peak load tariff, Renewable Energy System self-production, the variations in demand
 Periodic Reporting for period 1 - EnerMan (ENERgy-efficient manufacturing system MANagement) Result title Periodic Reporting for period 1 - EnerMan (ENERgy-efficient manufacturing system MANagement)
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Description The iPRODUCE platform will be deployed in six local 'ecosystems' which cover different levels of maturity with collaborative production, diverse objectives and application areas spanning from home
Comments MIE Consultation 2020 (Closed) R&I Objective 2.3: Manufacturing with new and substitute materials MIE Consultation 2020 (Closed) Specific Objective 2: Circular products & Climate-neutral manufacturing
 cMDFs manufacturing capability map and repository Result title cMDFs manufacturing capability map and repository Result description cMDFs manufacturing capability map and repository
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Description The proposed approach is underpinned by predictive and prescriptive AI analytics at both component and system level, by cross-fertilizing edge and platform AI, while leveraging the human knowledge and
Organisation INEOS MANUFACTURING BELGIUM BV
 AI-PROFICIENT system architecture Result title AI-PROFICIENT system architecture
 AI4Manufacturing (ICT-38-2020) Project Cluster - 18 February 2022 - ConnectedFactories event Result description AI4Manufacturing (ICT-38-2020) Project Cluster: Ioannis Soldatos, Intrasoft. Recording and presentation from the ConnectedFactories online event on 18 February 2022
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Description The main objective of InterQ project is to measure, predict and control the quality of the manufactured products, manufacturing processes and gathered data to assure Zero-Defect-Manufacturing by means
Comments : Human & technology complementarity and excellence in manufacturing MIE Consultation 2020 (Closed) Specific Objective 4: Human-centered and human-driven manufacturing innovation
 FINGERPRINT: MACHINE TOOL CONDITION MONITORING APPROACH FOR ZERO DEFECT MANUFACTURING Result title FINGERPRINT: MACHINE TOOL CONDITION MONITORING APPROACH FOR ZERO DEFECT MANUFACTURING
 Test Bench for Automated forged gear inspection Result description The system is based on the UT technology that allows the detection of small and complex defects thanks to the inspection strategy defined in the system.
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Description ECOFACT aims at enabling manufacturing industries to optimize the energy performance of their production systems in line with their relevant production constraints (time and resources), while at the same
Organisation COMPETENCE INDUSTRY MANUFACTURING 40 (CIM 4.0)
 Periodic Reporting for period 2 - ECOFACT (ECO-innovative Energy FACTory Management System based on enhanced LCA and LCCA towards resource-efficient manufacturing) Result title Periodic Reporting for period 2 - ECOFACT (ECO-innovative Energy FACTory Management System based on enhanced LCA and LCCA towards resource-efficient manufacturing)
 Mapping of manufacturing sectors for ECOFACT application Result description Mapping of manufacturing sectors for ECOFACT application
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Description This will drastically improve the resilience and long term sustainability of highly complex manufacturing facilities to foreseen and unforeseen disturbances and deteriorations thereby minimising energy
Organisation THE MANUFACTURING TECHNOLOGY CENTRE LIMITED LBG
Comments and resource-efficient manufacturing equipment FoF Partnership SRIA Research priorities Sub-Domain 2.1 Adaptive and smart manufacturing devices, components and machines Domain 2: Adaptive and smart manufacturing
 Final Report Summary - SELSUS (Health Monitoring and Life-Long Capability Management for SELf-SUStaining Manufacturing Systems) Result title Final Report Summary - SELSUS (Health Monitoring and Life-Long Capability Management for SELf-SUStaining Manufacturing Systems)
 Domain 2: Adaptive and smart manufacturing systems Taxon title Domain 2: Adaptive and smart manufacturing systems Taxon description The set of research priorities under this domain focuses on innovative manufacturing equipment at component and system level, including mechatronics, control and monitoring systems The research priorities
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Description The control system will include pre- and post-welding measurement as well as in-process monitoring, control and fault prevention / fixing.
Organisation THE MANUFACTURING TECHNOLOGY CENTRE LIMITED LBG
Comments Domain 1 - Advanced Manufacturing Processes Impact Workshop D1-Area 3: Laser-based Manufacturing Impact Workshop Domain 1 - Advanced Manufacturing Processes Domain 1: Advanced manufacturing processes
 Laser Welding at CRF: from research to manufacturing plant Result title Laser Welding at CRF: from research to manufacturing plant Result description RADICLE presentation elaborated with a project partner, showcasing the benefits gathered from the projects' outcomes, displaying the development of the system from research to manufacturing plant.
 Domain 1: Advanced manufacturing processes Taxon title Domain 1: Advanced manufacturing processes
 RP 1.6 Material efficient Manufacturing processes Taxon description Increasing the material efficiency can be developed at different levels of manufacturing system through: (i) Process modification, (ii) On site recovery and reuse of waste materials and (iii) Transformation
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Description and operation absence of adaptable control to accurately handle a variety of workpieces and materials, and inefficiency of planning systems in addressing holistically all hierarchical production levels
Organisation TEACHING FACTORY COMPETENCE CENTERUPSKILLING AND TRAINING DEVELOPMENTAND IMPLEMENTATION OF ADVANCED TECHNOLOGIES FOR THE MANUFACTURING IND
 Variform large part packaging - Metal production pilot case Result description Intelligent fixtures and machine learning algorithms will enhance the system’s performance for new product variants.
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Comments manufacturing RP 5.2 Advanced Information Models for knowledge creation and learning FoF Partnership SRIA Research priorities Domain 5: Human-centric manufacturing RP 5.3 Levels of automation and continuous
 The MAS Tracker Result description The tracker is designed to be easily tagged to any manufacturing workpiece. It is easily programmed with a new workpiece serial number using a dedicated iPad/iPhone App.
 RP 5.3 Levels of automation and continuous adaptation of workplaces Taxon title RP 5.3 Levels of automation and continuous adaptation of workplaces
 RP 5.7 Future tools for human activity monitoring and analysis Taxon description The complexity of processes in manufacturing requires optimization at different levels.
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Description Traditional manufacturing industry is in the throes of a digital transformation.
Comments Integrated Decision Support System (ABE) 4. Visual Analytics Tool (CERTH) 5. Social Collaboration platform with Gamified Actions (CERTH/FIT) 6. Ergonomics Tool (CERTH) 7.
 Augmented Reality wearable computing and gamification in manufacturing industries Result title Augmented Reality wearable computing and gamification in manufacturing industries
 iDSS-Decision Support System for Incident Detection and Maintenance in Industries Result description The Integrated Decision-Support-System for Incident Detection and Maintenance in Industries-iDSS uses semantic modelling of manufacturing knowledge spaces and processes, of shop floor actors and machinery
 DELIVERABLE D2.1 - SatisFactory System Architecture Result acronym SatisFactory - System Architecture
 C MANUFACTURING Taxon title C MANUFACTURING
 RP 5.7 Future tools for human activity monitoring and analysis Taxon description The complexity of processes in manufacturing requires optimization at different levels.
 Number of project results taken-up for higher TRLs using additional investments Comments Integrated Decision Support System (ABE) 4. Visual Analytics Tool (CERTH) 5. Social Collaboration platform with Gamified Actions (CERTH/FIT) 6. Ergonomics Tool (CERTH) 7.
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Description The technology that is being developed in the project will include a new sensor system for robust detection of fibre orientation combined with a robotic system to scan complex parts.
Comments - Web and social networking Success Factors Communication (COMMUNIC) Number of patent applications Additional KPIs The fibre angle sensor is patented, the remaining parts constitute a whole robotic system
 Robot for Measuring Fibre Angles on complex 3D pre-form parts Result description A robotic system is equipped with a fibre-angle measurement sensor. This sensor provides a dense mapping for fibre angles within a a grid size of about 50um in a field of view of about 40cm².
 C MANUFACTURING Taxon title C MANUFACTURING
 RP 1.6 Material efficient Manufacturing processes Taxon description Increasing the material efficiency can be developed at different levels of manufacturing system through: (i) Process modification, (ii) On site recovery and reuse of waste materials and (iii) Transformation
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Description The METAMORPHA concept is a single agile USP laser micromachining platform to replace many conventional manufacturing process chains.
 Periodic Reporting for period 1 - METAMORPHA (Made-to-measure micromachining with laser beams tailored in amplitude and phase) Result description The METAMORPHA project was initiated with the goal of addressing the limitations and drawbacks of conventional manufacturing processes.
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Description The project aimed to create a sustainable test bed that strengthens Swedish industry by providing facilities and tools to physically and virtually test and evaluate different manufacturing concepts.
Comments Novel materials Manufacturing future products Manufacturing the products of the future Customised products Manufacturing future products Manufacturing the products of the future Resource efficient, sustainable
 Additive manufacturing Taxon title Additive manufacturing
 RP 1.6 Material efficient Manufacturing processes Taxon description Increasing the material efficiency can be developed at different levels of manufacturing system through: (i) Process modification, (ii) On site recovery and reuse of waste materials and (iii) Transformation
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Description Fourth, FALCON will explore manufacturing intelligence to support innovative product-services design and finally FALCON will improve product-service lifecycle assessment approaches through the real-time
Comments Knowledge-workers and operators Technologies and enablers System modelling - digital twins, simulation Technologies and enablers Engineering tools FALCON aims to provide methodologies and approaches
 The FALCON Ontology Result description The FALCON semantic model describes the basic entities of the project and model relevant structures of planning, design, engineering, manufacturing and exploitation processes.
 System modelling - digital twins, simulation Taxon title System modelling - digital twins, simulation Taxon description The model represents the system itself, whereas the simulation represents the operation of the system over time.