Introduction to the Aachen trial site of the EU-funded FINESCE project focusing on the demand side management in a smart factory, with a bit more detail on the use of FIWARE and Generic Enablers (GEs).

1. MANAGING SHOPFLOOR ENERGY
CONSUMPTION IN A SMART FACTORY
Using FIWARE for Demand Side Management
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2. In the Smart Factory we are
producing parts of an electric car
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StreetScooter Production of the underbody

3. The Smart Factory in Aachen
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§ Enable manufacturing sites to
become an intelligent load in
the smart grid
§ Create simple-­to-­use and fast-­
to-­scale energy management
infrastructure
§ Demonstration factory with
direct shopfloor access
§ Production of prototypes and
pilot series to be sold
§ Monitoring of energy
consumption of machines
Objectives
Factory setup
Laser cutting machine
Bending machine

4. FIWARE GEs are used on different
layers to support integration
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Data interpretation layer
Robots
Machine
tools
Assembly
stations
Connection
to the VPP
Real-­time and high-­
resolution data collection
Visualisation and
decision memos
Goal of the integration
Data gathering layer
Data exploitation layer
Overall architecture

5. Integration of the GEs with good
progress and results
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* Enterprise-­Resource-­Planning, the key business management software
for manufacturing companies
Data
interpretation
layer
Data
exploitation
layer
Data
gathering
layer
GEs and DSEs
§ GE Gateway Data Handling (D, on-­premise)
§ DSE OBDC Event Sink (on-­premise, OS)
§ DSE Modbus Adapter (on-­premise, PS)
§ GE Complex Event Processing (D, FI-­Lab)
§ GE Publish/Subscribe Broker (D, FI-­Lab)
§ GE Big Data Analysis (E, FI-­Lab)
§ GE Object Storage (E, FI-­Lab)
§ GE Application Mashup (U, FI-­Lab)
§ DSE Production Planning and Control System
Integrator (on-­premise, under discussion)

6. Reminder: The GE Gateway Data
Handling gathers shopfloor data
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Data
interpretation
layer
Data
exploitation
layer
Data
gathering
layer
Factory Server
Machine
tool or
robot
Machine
tool or
robot
Measuring
device
Production Site Network (ethernet based)
Shopfloor
device for
operator
feedback
SPS/
CPS
Shopfloor Industrial PC
PROFINET Modbus Modbus
Data
collector
Modbus
Temporary
Storage
(Proprietary)
Manufacturing
Execution System
PROFINET
TCP
Socket
Modbus
Adapter
TCP
Socket
GE
Gateway Data Handling
(locally deployed)
HTTP
REST
API
DSE
Modbus Adapter
Northbound event propagation
to FI-­WARE Cloud
HTTP
REST Local
Research
Database
OBDC
Event Sink
DSE
OBDC Event Sink

7. Assessment of the
GE Gateway Data Handling
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0%
20%
40%
60%
80%
100%
Functional
suitability
Performance
efficiency
Compatibility
Usability
Reliability
Security
Maintainability
Portability The GE Gateway
Data Handling
showed a very good
overall result (83,85%)
and greatly supports a
fast and scalable
integration of energy
management in an
industrial
environment!

8. The interpretation layer is
implemented and mainly consists of
GEs
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Data
interpretation
layer
Data
exploitation
layer
Data
gathering
layer
Northbound event propagation
to FI-­WARE Cloud
Enterprise
Resource
Planning
Energy
Efficiency
Module
Energy KPI
Module
Production
Visualization
GE
Complex Event
Processing (CEP)
GE
Publish/ Subscribe
Context Broker
Open interface
for events
Production
database
Smart Factory API
Open interface
for historic data

9. Deep-­dive: The CEP performs good
compared to commercial alternatives
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Several commercial alternatives
Apama
Analytics &
Decisions
Platform
Alternatives in the research community
Evaluation in FINESCE WP3-­Smart Factory
Functional suitability: Query Language fulfils
all requirements in the trial
Performance efficiency: Easily manages load
Compatibility: Out-­of-­the-­box with Pub/ Sub
Context Broker, REST API
Usability: Text-­intensive interface with good
structure
Reliability: No problems in trial experienced
Maintainability: No problems in maintenance
so far
Portability: Standardized interfaces based on
established technologies

10. iPad App to visualise factory
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11. Page 11
kthxbai
Julian Krenge
Julian.Krenge@gmail.com
+49 171 55 11 577