A KPI monitoring system has been developed to monitor the critical performance of a real factory automation testbed. Future work Setting thresholds (targets) for KPIs Alarm mechanism to announce interesting behaviors Conversion of shop floor and MES information into meaningful pieces of advices

1. Embedded Service Oriented
Monitoring for the Energy Aware
Factory
•Date: September, 2012 Conference: 2012 IEEE International
•Linked to: eSONIA Conference on Information and
Automation for Sustainability
Title of the paper: Embedded Service
Oriented Monitoring for the Energy Aware
Factory
Authors: Corina Postelnicu, Bin Zhang,
Contact information Jose Luis Martinez Lastra
Tampere University of Technology,
FAST Laboratory,
P.O. Box 600, If you would like to receive a reprint of
FIN-33101 Tampere, the original paper, please contact us
Finland
Email: fast@tut.fi
www.tut.fi/fast
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2. Embedded Service
Oriented Monitoring for the
Energy Aware Factory
Corina Postelnicu
Bin Zhang
Jose L. Martinez Lastra
Factory Automation Systems and Technologies
Tampere University of Technology, Finland
ICIAfS 2012, Beijing, China
27-29.9.2012
ARTEMIS eSONIA project (Embedded Service Oriented Monitoring, Diagnostics and Control: Towards the
Asset Aware and Self Recovery Factory)

3. Outline
1.Introduction
2.The model
3.Testbed
4.Implementation
– Technologies
– Complex Event Processing
– Key Performance Indicators
5.Conclusions and future work
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4. Introduction
1.Requirements for modern manufacturing
systems
Flexibility, Efficiency, Etc
2.Energy 2020 strategy by European Council in
March 2007
1. Reduce total energy use by 20%
2. Increase renewable energy use to 20%
3. Reduce greenhouse gas emission by 20%
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5. Introduction
Solution
1.Define Key Performance Indicators (KPIs)
2.To gather and process data in real time to
KPIs
3.To display KPIs in real-time on web
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6. The model
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7. Testbed
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8. Testbed
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9. Testbed
+ +
+ +
+ +
+ +
= 729 product variants
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10. Testbed
Embedded controllers to publish the device information as
web services
Each cell has 4 controllers
Cell 1 has an extra controller
Energy
consumption
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11. Implementation:
Technologies
SOAP WS
Runtime KPIs
Web application
Data persistence
Visualization
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12. Implementation: Complex
Event Processing
Event Processing Language (EPL): Listener:
select a.cellId as cellId, a.dateTime as dateTime, ….
b.AWATTHR as energy, a.palletId as palletId public void update(Map map){
from pattern [ every a=EquipmentChangeState String cellId = map.get(“cellId”).toString();
(currentState="READY-PROCESSING- ….
EXECUTING") -> b=EnergyMeter(cellId=a.cellId)] }
Rules Listeners
Event flow Esper Engine
Event
registration As the events flowing to the
engine, a match on the
EPL invokes the update
method in the Listener.
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13. Implementation: Key
Performance Indicators
 Efficiency  Energy
– Unit energy consumption • Cell energy consumption
– Process energy • Unit energy consumption
consumption
– Unit production time
– Unit processing time
– Production shutdowns
– Cell production rate
 Reliability  Quality
• Mean time-to-repair (MTTR) • Frame quality rate
• Mean time-to-failure (MTTF) • Keyboard quality rate
• Mean time between failure • Screen quality rate
(MTBF) • Overall quality rate
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14. Conclusions and future work
A KPI monitoring system has been developed
to monitor the critical performance of a real
factory automation testbed.
Future work
1. Setting thresholds (targets) for KPIs
2. Alarm mechanism to announce interesting
behaviors
3. Conversion of shop floor and MES information
into meaningful pieces of advices
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Energy Aware Factory

15. Thank you!
corina.postelnicu@tut.fi
bin.zhang@tut.fi
ARTEMIS eSONIA project (Embedded Service Oriented Monitoring, Diagnostics and Control: Towards the
Asset Aware and Self Recovery Factory)
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