in Automated Manufacturing Kira Barton Department of Mechanical Engineering University of Michigan November 3 rd 2016 Data flow in automated manufacturing Current Manufacturing Automation ID: 533130
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Slide1
Latency and Communication Challenges in Automated Manufacturing
Kira Barton
Department of Mechanical Engineering
University of Michigan
November 3
rd
, 2016Slide2
Data flow in automated manufacturingSlide3
Current Manufacturing Automation
Digital Manufacturing – new enabling technologies:
Cloud computing
Internet of things
MTConnect
Virtualization
Service-oriented architecturesAdvanced computing technologiesSlide4
Current Manufacturing Automation
Increased requirements on latency and communicationSlide5
Challenges with Real-time Data - GMSlide6
What to collect ?
Smart Sensing?
Sensing Real-time
Data
Inventory
People
Machines
Challenges with Real-time Data - GMSlide7
Challenges with Real-time Data - GM
What to collect ?
Smart Sensing?
Main Server
Internet
Plant Monitoring & Control
What/When/Where to transfer
?
How to provide feedback?
Sensing Real-time
Data
Inventory
People
MachinesSlide8
Challenges with Real-time Data - GM
Real-time
Data
Remote Monitoring
&
Control
What to monitor
?
How to analyze
?
How to control?
Analysis
What to
collect?
Smart Sensing?
Main Server
Internet
Plant Monitoring & Control
What/When/Where to transfer
?
How to provide feedback?
Sensing Real-time
Data
Inventory
People
MachinesSlide9
Challenges with Real-time Data - GM
Real-time Data
Product & Mfg.
Engineering
PLANNING
DESIGN
Maintenance
Anomaly detection
Learning
What to do with the information?
Decision making?
Real-time
Data
Remote Monitoring
&
Control
What to monitor
?
How to analyze
?
How to control?
Analysis
What to
collect?
Smart Sensing?
Main Server
Internet
Plant Monitoring & Control
What/When/Where to transfer
?
How to provide feedback?
Sensing Real-time
Data
Inventory
People
MachinesSlide10
What to
Communicate and how?
Challenges with Real-time Data - GM
Real-time Data
Product & Mfg.
Engineering
PLANNING
DESIGN
Maintenance
Anomaly detection
Learning
What to do with the information?
Decision making?
Real-time
Data
Remote Monitoring
&
Control
What to monitor
?
How to analyze
?
How to control?
Analysis
What to
collect?
Smart Sensing?
Main Server
Internet
Plant Monitoring & Control
What/When/Where to transfer
?
How to provide feedback?
Sensing Real-time
Data
Inventory
People
MachinesSlide11
1.
Which
sensors
to include at
each level
–
Machine, cell, system, factory
How
to convert and transfer data between enterprise levels?
What
are communication needs and latency impacts?
Control
: high fidelity for decision making
Diagnostics
: data storage, analytics, learning
Safety
: fast and accurate response times
Network requirements to be addressedSlide12
Network Partitioning for Control, Diagnostics and Safety on Ethernet
Ethernet I/O functionality domains
Control
:
Medium
data volumes, high determinism
Diagnostics
: High
data volumes, high speeds, low determinism
Safety
:
Small
data volumes, very high determinismSlide13
Network Partitioning for Control, Diagnostics and Safety on Ethernet
Central Switch
System Switch
System Switch
Control
Control
Control
Control
Control
Secure Cloud Infrastructure
Firewall
Machine level
Sensing
Control levelSlide14
Network Partitioning for Control, Diagnostics and Safety on Ethernet
Central Switch
System Switch
System Switch
Control
Control
Control
Control
Control
Secure Cloud Infrastructure
Firewall
Machine level
Sensing
Control level
Timing mismatch
Network congestion
Poor network provisioning
Noisy signals
Data lossSlide15
Network End-to-End Performance Cost
P
B
P
A
P
C
Continuous Control
A
Digital Control
Performance: Tracking Error
Worse
Better
Sampling Time
Larger
Smaller
Acceptable
Out of Control
Networked
Control
B
C
Impact of sampling & additional delays
Network saturation inducing longer delays
Unacceptable
Ideal
Operating
Region
Impact of samplingSlide16
Can I use
TCP/IP versus
EtherNet
/IP or
EtherCat
?
Should I partition my networks at different levels?
Should I put safety, control and diagnostics on one, two or three networks?
What is the tradeoff cost of a decision?
What is the performance cost of security
or
application level protocols
?
What is the tradeoff complexity of a decision?
What are the industry defacto standards?
Where is the delay and delay variability occurring?
Issues driving network performanceSlide17
Current methods to address issues
Time synchronization algorithms
close
to the production
tasks
strict
requirements on
timing
n
eed context to the data to align timing
Event-based control
mitigate
logic errors
may result in time delays
Multiplex network scheduling
utilize alternative network interfaces for communication
t
ransmit over path with smallest estimated delay
Improve software to address delays and communication issuesSlide18
Automated manufacturing network requirements
Data transfer rate
Data
transfer load
Impact
of delays
Multi-plex capabilities
Low-level Control (CNC, robots,
etc.)
1ms or faster
Medium
Critical
(performance)
Typically
noHigh-level control (PLCs)
~10msLowCritical (performance)
Typically noDiagnosticsSlowHighMinimalYesSafety
FastLowCriticalPotentiallySlide19
Thank you for your attention!
Questions?