the power of the edge for smart manufacturing
TRANSCRIPT
![Page 1: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/1.jpg)
The Power of the Edge for Smart Manufacturing
Shenyang, China18th August 2017
Paulo Leitã[email protected]
http://www.ipb.pt/~pleitao
![Page 2: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/2.jpg)
Agenda
2
1. Contextualization
2. Balancing cloud, fog and edge computing in Cyber-physical systems
3. Experiences in FP7 and H2020 R&D projects
4. Conclusions
![Page 3: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/3.jpg)
Agenda
3
1. Contextualization
![Page 4: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/4.jpg)
Evolution of complexity
4
Spirit of St. Louis,National Air and Space Museum, Smithsonian Institution
Airbus A380
![Page 5: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/5.jpg)
Complexity in engineering problems
5
Processes plants
Logistics
Smart grids
Taxis fleet
Manufacturing plants
Airport management
![Page 6: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/6.jpg)
New demands in manufacturing
6
1
Markets are imposing strong changing conditions Customization of products in high flexible production
Reduction of time to reconfigure(usually weeks and months)
Plug and produce Time on market / Time to
marketTesla’s robotic factory in Fremont, California
![Page 7: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/7.jpg)
Moving to decentralized structures
7
Traditionally: centralized and monolithic structures
Production processes
Sensors / actuators
Control
SCADA
MES
ERPANS/ISA
95
Challenge: decentralize and distribute functions
![Page 8: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/8.jpg)
Agenda
8
2. Balancing cloud, fog and edge computing in Cyber-physical systems
CREDIT: Getty Images
![Page 9: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/9.jpg)
9
Disruptive technologies enabling digitization
![Page 10: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/10.jpg)
Big data analytics
10
Huge volume of data is real time collected by a vast number of networked sensors using IoT technologies
Need to be managed in real time and not too late Data analytics to: Detect earlier possible problems (defects, disturbances)
Detect trends, patterns aiming prediction and optimization
Visible data
Hidden meaning and content
sea
![Page 11: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/11.jpg)
Data analytics only performed in the cloud?
11
Cloud computing is not the solution for
everything
What happen if the connection to the cloud fails?
![Page 12: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/12.jpg)
Why do we need intelligence at the edge?
12
IoT devices are connected to “places” where data is generated
Some data should be processed as close as possible to originating source and in real-time
Performing analytics to make real-time decisions Supporting real-time requirements Mitigating communication failures
Pre-processing and filtering to reduce the exchanged data size Optimizing the bandwidth Reducing the storage costs
![Page 13: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/13.jpg)
Aligned with Industrial Trends
13
“We should not send all collected data to be processed in the cloud but instead to make analysis in the edge”
James Truchard, National Instruments @IFAC IMS’16
“Define data collection requirements to minimize the collection of ‘big data’”
“Enable feedback of intelligence through the system to update control for optimal production”
Brian Weiss, NIST @IFAC IMS’16
“Analyzing data close to the device that collected the data can make the difference between averting disaster and a cascading system failure”
Cisco, White paper, 2015
![Page 14: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/14.jpg)
Challenge to implement industrial IoTsolutions
14
Use different layers to distribute intelligence and perform data analytics, e.g., Combine cloud computing and edge computing
Consider fog computing (intermediate layers)
Cloud computing
Edge computing
Fog computingembedding
intelligence in IoT devices
embedding intelligence in
network devices, e.g., firewalls
![Page 15: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/15.jpg)
The role of edge vs cloud
15
• Processing as close to source as possible
• Real-time monitoring and decision-making
• Fast response to condition change
• Data pre-processing and filtering
Cloud layer Edge layer
• Central data aggregation
• Long-term data processing
• Historical analysis of data
• Optimization and prediction
![Page 16: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/16.jpg)
MAS for distributed intelligence
16local scope
Individual local behaviour
Global function emerges from interaction among
entities
Society of intelligent autonomous and cooperative entities
Modularity and reconfiguration is easy!
![Page 17: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/17.jpg)
Agents distributed among different levels
17
Cloud level to make accurate and
optimized analysis
Edge and fog levels to make a fast (real-
time) analysis
![Page 18: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/18.jpg)
Challenges
18
How to balance intelligence among the cloud, fog and edge
layers?
How to handle data interoperability?
How to handle intelligence vs security and battery
autonomy in IoT devices?
![Page 19: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/19.jpg)
Agenda
19
3. Experiences in FP7 and H2020 R&D projects
![Page 20: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/20.jpg)
20
Objectives
Partners:
Integration of quality and process control in real-time
MAS infrastructure to support feedback control loops
![Page 21: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/21.jpg)
21
Functionalities
Preserving existing low-level control
Distributed collection of data in real-time
Correlation of data in real-time using data analysis
![Page 22: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/22.jpg)
22
Industrial deployment
MAS solution developed using JADE Installed in the Whirlpool’s factory plant producing
washing machines 11 QCAs and 6 RAs were running in PCs distributed
along the production line In stable production flow, approximately 400 PAs are
running simultaneously
![Page 23: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/23.jpg)
23
grace-demo
Examples of “intelligence” for data analysis
Early detection of non-conformities
Customization of functional tests according to the on-line gathered production data
Customization of the controller’s parameters of each machine considering the production data
Early detection of products that never reach desired quality
Dynamic adaptation of process parameters considering data gathered from quality control
![Page 24: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/24.jpg)
24
Main benefits
Increase of production efficiency
Reduction of non-conformities
Increase of products’ quality
Reduction of costs related to scraps
Increase of products’ customization
![Page 25: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/25.jpg)
25
Objectives
Partners:
ZDM strategies for multistage manufacturing Detect earlier possible problems to avoid the occurrence of
defects and their propagation
![Page 26: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/26.jpg)
26
Distributed data analysis
![Page 27: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/27.jpg)
27
Distributed data analysis
Cloud level to make accurate and optimized
analysis
Edge level to make a fast (real-time) analysis
![Page 28: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/28.jpg)
28
Industrial deployment
Resource agents running in NI sbRIO-9607, Raspberry PIs and industrial PCs
MAS solution developed using JADE 3 use cases: Auto Europa Volkswagen (assembly of tailgate and rear lights )
Electrolux (assembly line of professional ovens)
Zannini (high precision mechanical components)
OPC-UA and MQTT for transparency in data interoperability (loosed coupled among layers)
![Page 29: The Power of the Edge for Smart Manufacturing](https://reader036.vdocument.in/reader036/viewer/2022072118/62d9337912ae923b952f20d6/html5/thumbnails/29.jpg)
Conclusions
29
Edge computing allows enhancing IoT solutions
MAS suitable to implement distributed intelligence in CPS
Intelligence should be distributed by cloud, fog and edge computing layers
Think globally, act locally
Challenge: how is the balance among these layers?
A hard path is needed to face industrial challenges and requirements