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ReconCell

A Reconfigurable robot workCell for fast set-up of automated assembly processes in SMEs

Total Cost €

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EC-Contrib. €

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Partnership

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Project "ReconCell" data sheet

The following table provides information about the project.

Coordinator
INSTITUT JOZEF STEFAN 

Organization address
address: Jamova 39
city: LJUBLJANA
postcode: 1000
website: www.ijs.si

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Slovenia [SI]
 Project website http://www.reconcell.eu/
 Total cost 6˙306˙457 €
 EC max contribution 5˙561˙569 € (88%)
 Programme 1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
2. H2020-EU.2.1.5.1. (Technologies for Factories of the Future)
 Code Call H2020-FoF-2015
 Funding Scheme IA
 Starting year 2015
 Duration (year-month-day) from 2015-11-01   to  2019-02-28

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    INSTITUT JOZEF STEFAN SI (LJUBLJANA) coordinator 1˙002˙482.00
2    SYDDANSK UNIVERSITET DK (ODENSE M) participant 1˙080˙060.00
3    RHEINISCH-WESTFAELISCHE TECHNISCHE HOCHSCHULE AACHEN DE (AACHEN) participant 926˙980.00
4    GEORG-AUGUST-UNIVERSITAT GOTTINGENSTIFTUNG OFFENTLICHEN RECHTS DE (GOTTINGEN) participant 813˙975.00
5    BLUE OCEAN ROBOTICS APS DK (ODENSE M) participant 677˙488.00
6    INNOVAATION OY UUSI TEHDAS FI (TAMPERE) participant 381˙836.00
7    LOGICDATA ELECTRONIC & SOFTWARE ENTWICKLUNGS GMBH AT (DEUTSCHLANDSBERG) participant 241˙570.00
8    UAB PRECIZIKA METAL LT (VILNIUS) participant 222˙040.00
9    ELVEZ, PROIZVODNJA KABELSKE KONFEKCIJE IN PREDELAVA PLASTICNIH MAS DOO SI (VISNJA GORA) participant 215˙138.00

Map

 Project objective

ReconCell develops a new type of robot workcell, its required process infrastructures and the economic framework for automated robot assembly, especially designed for the needs of SMEs. SMEs would benefit from robotic automation, but often cannot use it due to set-up & maintenance complexity. This requires expert knowledge and time for configuration and programming, which is too costly for them. Robotic automation is, thus, normally economically infeasible for SMEs, especially for small batch sizes. ReconCell develops an easy to (re-)configure and (re-)program workcell, making robot solutions commercially viable even for small batch sizes (~1000 units) by reducing set-up & maintenance effort substantially.

Specifically, the ReconCell System is based on a layered concept where we start together with the customer with business modelling the planned product assembly based on the ReconCell System to assess its economic viability and provide decisive Key Performance Indicators (KPIs). On approval, the next layer of the ReconCell System implements assembly with automated testing in simulation. Here we use reconfigurable hardware elements to design the required workcell layout and assembly processes. After verification, product assembly takes place in the real workcell under machine vision-based monitoring and novel force-based control of execution to assure product quality using the KPIs. We demonstrate the capabilities of the layered ReconCell System on three real use cases provided by the SMEs of our consortium and two more use cases, established through an open call. In addition, the consortium has started to establish a network of potential ReconCell users to disseminate information about ReconCell technologies to all actors in the value chain, and to raise awareness about the possibilities of automated robot assembly in SMEs. The final aim is to establish a company that commercializes the workcell and associated technologies developed in the ReconCell project.

 Deliverables

List of deliverables.
Workcell monitoring: methods and evaluation Documents, reports 2020-01-21 12:43:49
Developer, Distribution & Manufacturing Network as well as new I4MS knowledge hubs establishments and operations Documents, reports 2020-01-21 12:43:48
Manual for setting up software tools for business intelligence Documents, reports 2020-01-21 12:43:49
Manual for workcell simulation Documents, reports 2020-01-21 12:43:48
Manual for programming of assembly skills and tasks Documents, reports 2020-01-21 12:43:48
Workcell simulation for reconfiguration Documents, reports 2020-01-21 12:43:48
Demonstration of optimal workcell reconfiguration in simulation Demonstrators, pilots, prototypes 2020-01-21 12:43:48
Manual for programming of visual processing Documents, reports 2020-01-21 12:43:48
Intermediate demonstrations of use-cases Demonstrators, pilots, prototypes 2020-01-21 12:43:48
Workcell installation manual Documents, reports 2020-01-21 12:43:48
Technical report on ReconCell model for business intelligence, part 2 Documents, reports 2020-01-21 12:43:48
Demonstration of optimal workcell reconfiguration in real world Demonstrators, pilots, prototypes 2020-01-21 12:43:48
Software environment for visual programming of assembly skills Demonstrators, pilots, prototypes 2020-01-21 12:43:47
ReconCell project website Websites, patent fillings, videos etc. 2020-01-21 12:43:47
Movement and grasping evaluation and learning through simulation Documents, reports 2020-01-21 12:43:47
Report on legal documents for partners, customers and developers Documents, reports 2020-01-21 12:43:47
Technical report on software and hardware components in the workcell Documents, reports 2020-01-21 12:43:47
Technical report on the design of innovative workcell elements Documents, reports 2020-01-21 12:43:48
Sub-system for 3D simulation, visualization and interfacing with the user Documents, reports 2020-01-21 12:43:47
Technical report on ReconCell model for business intelligence, part 1 Documents, reports 2020-01-21 12:43:48

Take a look to the deliverables list in detail:  detailed list of ReconCell deliverables.

 Publications

year authors and title journal last update
List of publications.
2018 Michael Schluse, Marc Priggemeyer, Linus Atorf, Juergen Rossmann
Experimentable Digital Twins—Streamlining Simulation-Based Systems Engineering for Industry 4.0
published pages: 1722-1731, ISSN: 1551-3203, DOI: 10.1109/tii.2018.2804917
IEEE Transactions on Industrial Informatics 14/4 2020-01-21
2017 Thiusius Rajeeth Savarimuthu, Anders Glent Buch, Christian Schlette, Nils Wantia, Jurgen Rossmann, David Martinez, Guillem Alenya, Carme Torras, Ales Ude, Bojan Nemec, Aljaz Kramberger, Florentin Worgotter, Eren Erdal Aksoy, Jeremie Papon, Simon Haller, Justus Piater, Norbert Kruger
Teaching a Robot the Semantics of Assembly Tasks
published pages: 1-23, ISSN: 2168-2216, DOI: 10.1109/TSMC.2016.2635479
IEEE Transactions on Systems, Man, and Cybernetics: Systems 2020-01-21
2018 Adam Wolniakowski, Andrej Gams, Lilita Kiforenko, Aljaž Kramberger, Dimitrios Chrysostomou, Ole Madsen, Konstantsin Miatliuk, Henrik Gordon Petersen, Frederik Hagelskjær, Anders Glent Buch, Aleš Ude, Norbert Krüger
Compensating Pose Uncertainties through Appropriate Gripper Finger Cutouts
published pages: 78-83, ISSN: 2300-5319, DOI: 10.2478/ama-2018-0013
Acta Mechanica et Automatica 12/1 2020-01-21
2017 Aljaž Kramberger, Andrej Gams, Bojan Nemec, Dimitrios Chrysostomou, Ole Madsen, Aleš Ude
Generalization of orientation trajectories and force-torque profiles for robotic assembly
published pages: 333-346, ISSN: 0921-8890, DOI: 10.1016/j.robot.2017.09.019
Robotics and Autonomous Systems 98 2020-01-21
2018 Michael Schluse, Marc Priggemeyer, Linus Atorf, Juergen Rossmann
Experimentable Digital Twins—Streamlining Simulation-Based Systems Engineering for Industry 4.0
published pages: 1722-1731, ISSN: 1551-3203, DOI: 10.1109/tii.2018.2804917
IEEE Transactions on Industrial Informatics 14/4 2020-01-21

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The information about "RECONCELL" are provided by the European Opendata Portal: CORDIS opendata.

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