Cooperating robots in manufacturing environmentslms.mech.upatras.gr/LMS/files-1/events/02 LMS... ·...
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Cooperating robots in manufacturing environmentsERF 2015, March 12, 2015, Vienna
Dr. George Michalos (LMS), Dr. Sotiris MAKRIS (LMS)
Aldo Botero (COMAU)
Laboratory for Manufacturing Systems and AutomationDirector: Professor G. Chryssolouris
University of PatrasGreece
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Laboratory for Manufacturing Systems and Automation
Director: Professor G. Chryssolouris
General Information
• LMS is involved in a number of research projects funded by the CEU and European industrial partners. Particular emphasis is given to the co-operation with the European industry as well as a number of "hi-tech" firms.
• LMS employs approximately 70 researchers organized in three different groups:
– Manufacturing Processes and Energy Efficiency
– Robots, Automation and Virtual Reality in Manufacturing
– Production Systems Planning, Control and Networking
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Laboratory for Manufacturing Systems and Automation
Director: Professor G. Chryssolouris
Cooperating robots for assembly
•Cooperating robots, are attractive for
• reducing the number of required fixtures
• shortening the process cycle time,
• whilst addressing the accessibility constraints introduced by the use of fixtures
•Their control is based either on the use of
• single controllers, capable of multi-tasking and controlling multiple robots or
• special frameworks, allowing standard controllers to cooperate with each other, by exchanging motion data, as well as synchronization and safety signals.
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Laboratory for Manufacturing Systems and Automation
Director: Professor G. Chryssolouris
Cooperating robots performing spot welding on automotive parts
•An illustrative example
•Two robots
•One is picking up and holding the parts to be welded,
•the second performs the spot welding operation.
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Laboratory for Manufacturing Systems and Automation
Director: Professor G. Chryssolouris
Challenges
• But....
• The control of cooperating robots should be more intelligently accomplished
• ICT infrastructure is required for managing the complexity of cooperation
• Achieving the required tolerances require use of sensors
Serv
ice
(SR
)
Control (C)Local Decisions
Auto adaptation
Networking (N)
Sensing (Sn)
So
ap
Sr CN
SnI/O
So
ap
2h maintenance
needed. Who
can perform the
handling?Estimated arrival
in 15 min.
Sr CSn
NI/O
Sr CSn
NI/O
So
ap
Do not have
suitable tools
Sr CSn
NI/O
Line Level
Reconfiguration
SrCSn
NI/O
Unit Level
Communication
Route part to
next station
Part grasped
securely
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Laboratory for Manufacturing Systems and Automation
Director: Professor G. Chryssolouris
Scenario of cooperative robots future factory
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Serv
ice
(SR
)
Control (C)Local Decisions
Auto adaptation
Networking (N)
Sensing (Sn)
So
ap
Sr CN
SnI/O
So
ap
2h maintenance
needed. Who can perform the
handling?Estimated arrival
in 15 min.
Sr CSn
NI/O
Sr CSn
NI/O
So
ap
Do not have
suitable tools
Sr CSn
NI/O
Line Level
Reconfiguration
SrCSn
NI/O
Unit Level
Communication
Route part to
next station
Part grasped
securely
– Automatically generate
assignments of tasks to robots
– Automatically generate
sequencing signals among
robots
– Automatically execute assigned
tasks
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Laboratory for Manufacturing Systems and Automation
Director: Professor G. Chryssolouris
AUTORECON – Automotive case
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Laboratory for Manufacturing Systems and Automation
Director: Professor G. Chryssolouris
AUTORECON – Vision correction
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Laboratory for Manufacturing Systems and Automation
Director: Professor G. Chryssolouris
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AUTORECON – Vision correction
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Laboratory for Manufacturing Systems and Automation
Director: Professor G. Chryssolouris
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AUTORECON – Vision correction
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Laboratory for Manufacturing Systems and Automation
Director: Professor G. Chryssolouris
Alternative cooperating robot architectures
• However....
• Alternative cooperating robots architectures are emerging
• Numerous applications can be managed in a more advanced way
• On going research on enhancing user interaction using sensors
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Laboratory for Manufacturing Systems and Automation
Director: Professor G. Chryssolouris
Service oriented architecture for integration
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Laboratory for Manufacturing Systems and Automation
Director: Professor G. Chryssolouris
Example
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Laboratory for Manufacturing Systems and Automation
Director: Professor G. Chryssolouris
AUTOnomous co-operative machines
for highly RECONfigurable assembly
operations of the future
http://www.autorecon.eu
Grant Agreement No: 285189
FoF.NMP.2011-2 “Cooperative machines and
open-architecture control systems”
Acknowledgements
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Laboratory for Manufacturing Systems and Automation
Director: Professor G. Chryssolouris
Expert cooperative robots for highly skilled operations for the
factory of the future
http://www.xact-project.eu
Research has received funding from the
European Union's 7th Framework
Programme (FP7/2007-2013) under grant
agreement n°314355
X-act
Acknowledgements
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Laboratory for Manufacturing Systems and Automation
Director: Professor G. Chryssolouris
Flexible assembly processes for the Car of the Third
Millennium
http://www.mycar-project.eu
Research has received funding from the
European Union's 6th Framework Programme
under grant agreement n°026631
Acknowledgements
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THANK YOU!
Laboratory for Manufacturing Systems and AutomationDirector: Professor G. Chryssolouris
University of PatrasTel: +30-2610-997262
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Laboratory for Manufacturing Systems and Automation
Director: Professor G. Chryssolouris
References
• S. Makris, G. Michalos, G. Chryssolouris, “RFID driven robotic assembly for random mix manufacturing”, Robotics and ComputerIntegrated Manufacturing, Volume 28, Issue 3, June 2012, 359-365.
• S. Makris, G. Michalos and G. Chryssolouris, “Virtual Commissioning of an assembly cell with cooperating robots”, Advances in Decision Sciences, vol. 2012, Article ID 428060, 11 pages, 2012. doi:10.1155/2012/428060.
• G. Michalos, S. Makris, N. Papakostas, D. Mourtzis, G. Chryssolouris, “Automotive assembly technologies review: challenges and outlook for a flexible and adaptive approach”, CIRP Journal of Manufacturing Science and Technology, Volume 2, Issue 2, 2010, Pages 81-91 DOI: 10.1016/j.cirpj.2009.12.001.
• N. Papakostas, G. Michalos, S. Makris, D. Zouzias and G. Chryssolouris, “Industrial Applications with Cooperating Robots for the Flexible Assembly”, International Journal of Computer Integrated Manufacturing, Vol. 24, No. 7, July 2011, 650–660
• G. Michalos, S. Makris, D. Mourtzis, “An intelligent search algorithm based method to derive assembly line design alternatives”,International Journal of Computer Integrated Manufacturing, Volume 25, Issue 3, 2012, 211 -229
• N. Papakostas, D. Mourtzis, G. Michalos, S. Makris, G. Chryssolouris, “An agent-based methodology for manufacturing decision-making: A textile case study”, International Journal of Computer Integrated Manufacturing, , Volume 25, Issue 6, 2012, 509-526.
• S. Makris, G. Pintzos, L. Rentzos, G. Chryssolouris, “Assembly support using AR technology based on automatic sequence generation”, CIRP Annals - Manufacturing Technology, Volume 62, Volume 1, 2013, Pages 9-12.
• D. Mourtzis, N. Papakostas, D. Mavrikios, S. Makris, K. Alexopoulos, “The role of simulation in digital manufacturing – applications and outlook”, International journal of computer integrated manufacturing
• S. Makris, P. Tsarouchi, D. Surdilovic, J. Krueger, “Intuitive Dual arm robot programming for assembly operations”, to appear in CIRP Annals – Manufacturing Technology, Vol. 63, Issue 1, (2014)
• P. Tsarouchi, G. Michalos, S. Makris, G. Chryssolouris, Vision System for Robotic Handling of Randomly Placed Objects, Procedia CIRP, Volume 9, 2013, Pages 61-66.
• G. Michalos, S. Makris, P. Aivaliotis, S. Matthaiakis, A. Sardelis, G. Chryssolouris, Autonomous production systems using open architectures and mobile robotic structures, Procedia CIRP, 2014.
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Cooperating robots challenges
•Coordination, sequencing, collision and communication architectures.
•Real time motion coordination and communication between robot controllers requires higher computational capabilities from the robot controller side as well as protocols for high speed signal exchange.
•The programming aspects of such systems are characterized by higher complexity since programmers need to consider the dynamic nature of real time communication between robots during the generation of code for the control of the robots.
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