Conference: 2012 IEEE International Conference on Industrial Informatics
Title of the paper: A cross-layer approach to energy management in manufacturing
Authors: Anna Florea, Jorge A. Garcia Izaguirre Montemayor, Corina Postelnicu, Jose L. Martinez Lastra
A cross-layer approach to energy management in manufacturing
1. A cross-layer approach to energy
management in manufacturing
Date: July, 2012 Conference: 2012 IEEE International
Linked to: RTD research at FAST Conference on Industrial Informatics
Title of the paper: A cross-layer
approach to energy management in
manufacturing
Authors: Anna Florea, Jorge A. Garcia
Izaguirre Montemayor, Corina Postelnicu,
Jose L. Martinez Lastra
Contact information
Tampere University of Technology,
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the original paper, please contact us
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2. A cross-layer approach to energy management in
manufacturing
Anna Florea
Jorge A. Garcia Izaguirre Montemayor
Corina Postelnicu
Jose L. Martinez Lastra
Tampere University of Technology, Finland
3. Outline
Background + The addressed problem.
Proposed Architecture for Cross-layer Energy
Management
Summary
4. Background
The distributed manufacturing enterprise
Contributors to overall energy consumption:
Manufacturing equipment
Collaboration / Competition patterns between devices/factories
5. Background
The distributed manufacturing enterprise
Contributors to overall energy consumption:
Manufacturing equipment
Collaboration / Competition patterns between devices/factories
+ Buildings
+ Personnel
Saving opportunities
Integration challenges
Increased time/cost
6. Background
Saving opportunities
Rerouting the solar energy acquired by the building to the MES
system because e.g.
Energy prices in a certain time range are high and
the energy required to heat/illuminate the building need
not be so much ( humans do not usually reside in the area at
that time slot of the day)
7. Cross layer Energy Management
Proposed Architecture
long term strategic
efficiency objectives
Business relevant targets
Reports
short-term optimisation
based on:
Service Oriented Architecture (SOA)
Complex Event Processing (CEP)
10. Summary
cross-layer approach proposed for Energy Management
Systems implementation in manufacturing enterprises
SOA 2.0 technologies
Web Services for implementation of data acquisition
from heterogeneous sources, and exposure of
reporting tools
Complex Event Processing for analysis and reasoning
towards improved energy performance.
13. Related work
framework based on ISO 9000 and ISO 14000 quality and
environmental management standards
to facilitate EMS design:
EN 16001:2009 Energy Management Systems
ISO 50001: Energy managements systems – Requirements with
guidance for use.
EMS focus either on particular industrial sites or specific energy
sources
lack of infrastructure resulting in a failure to allow real-time decision
making based on on-line information coupled with business
processes
Notes de l'éditeur
Rerouting the solar energy acquired by the building to the MES system because e.g. Energy prices in a certain time range are high and the energy required to heat/illuminate the building need not be so much because humans do not reside in the area at that time slot of the day
DAE collecting relevant data from BA and FA systems, computation of Key Performance Indicators (KPI) and storing this data in the corresponding (BAS or FAS) database. DSS fwd process chaining evaluates the acquired data and calculated KPI values with respect to the objectives defined in the Knowledge Base, stored in dedicated database, and suggests actions for performance improvement. SYNC check is done whether DSS output may propagate down to BAS and FAS.
eEMS Report Engine to build and provide consolidated reports after accessing the database to obtain the required information. The RE functionality can be exposed as web service to the users.Reasoning in eEMS is to be implemented by means of a CEP engine, having the database as input and internal Knowledge Base, stored in dedicated database of CEP engine, for reasoning. The CEP engine analyzes energy consumption patterns, passes the refined information to other ERP systems, and updates the Knowledge Base of mEMS if needed.
Approaches to modelling and knowledge representation are out of the scope of present paper.