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Supporting Smart Manufacturing by enabling
›lot size one manufacturing›decision-making for real time actions›integration of robotic and additive manufacturing technologies›higher levels of connectivity›advanced integrated control and online planning›real time simulation and optimization,combining machine-learning with simulation-optimization approaches
Project Coordinator - Europe César Toscano [INESC TEC][email protected]
Project Coordinator - BrazilMauro Rosa [INESC P&D Brasil][email protected]
Project Website www.fastenmanufacturing.eu
LinkedInwww.linkedin.com/company/fastenmanufacturing
ResearchGate www.researchgate.net/project/FASTEN-Flexible-and-Autonomous-Manufacturing-Systems-for-Custom-Designed-Products
Flexible and Scalable Robotic and Additive Manufacturing System
Open Industrial IoT Platform for Custom-designed Products
Predictive and Prescriptive Analytic Tool
Holistic Simulator-Optimizer Tool
Real-time Monitoring and Performance Management Tool
The FASTEN Framework
Contacts
Flexible and Autonomous Manufacturing Systems for Custom-Designed Products
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Grant Agreement Nº 777096
FASTEN “mission” is to develop, demonstrate, validate, and disseminate an integrated and open modular framework for efficiently producing highly customized products.
This will be achieved by pairing digital integrated service/products to additive manufacturing processes, on top of tools for decentralizing decision-making and data interchange.
Software technologies will be applied to build a fully connected additive manufacturing system by exploiting robotic, automation, simulation, as well as optimization and prescriptive analytics technologies.
Demonstration of these technologies will be performed in two pilot cases: ThyssenKrupp Elevadores in Brazil and Embraer Portugal in Europe (aeronautics).
FASTEN Consortium
Overview
Impact at THYSSENKRUPP ElevadoresTo increase the responsiveness, flexibility and scalability of maintenance activities by
›developing a Smart Robotic Additive Manufacturing Unit, composed of IoT-enhanced 3D printers and Mobile Robotic Manipulators, able to produce real time spare parts demands.
›exploiting a set of Optimization, Simulation and Predictive tools capable of optimal manufacturing network system configuration and spare parts production scheduling.
Rio Grande do Sul›Pontifícia Universidade Católica do Rio Grande do Sul›Thyssenkrupp Elevadores SA
BahiaUniversidade Federal da Bahia
Goiás›Bradel Distribuição›Universidade Federal de Goiás
São Paulo›INESC P&D Brasil›Embraer S.A.
Santa CatarinaUniversidade Federalde Santa Catarina
GermanyPACE Aerospace Engineering and Information Technology
Italy›Politecnico Di Milano›Intellimech
Portugal›INESC TEC-Institute for Systems and Computer Engineering, Technology and Science›EMBRAER Portugal, S.A.
Impact at EMBRAERTo increase the responsiveness, flexibility and scalability of logistic/production activities by
›to provide higher efficiency in warehouse/logistics operations by automating the current manual Kit Assembling activity through an IoT enhanced Pick & Place Collaborative Robot (Collabot) able to handle diverse parts.
›to shorten the time for decision making on disruption management situations related to the wing assembly line by continuously harnessing data from the assembly line and coordinating Simulation, Optimization and Prediction tools.