3 Ways To Make Your Factory Smarter With IIoTfiles.microscan.com/resources/3 Ways To Make...
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3 Ways To Make Your Factory Smarter With IIoT
Christoph Wimmer
Omron Microscan#AdvMfgExpo
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Founder – Dr. Kazuma TateisiTo the machine, give the work. To people, give the thrill of creation.
Kazuma Tateisi, Founder
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Defining “IoT”
“If we had computers that knew everything there was to know about things—using data they gathered without any help from us—we would be able to track and count everything, and greatly reduce waste, loss and cost. We would know when things needed replacing, repairing or recalling, and whether they were fresh or past their best.”
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Industrial IoTAdditional considerations for…
• Production Environment
• Legacy Assets
• Data Privacy & Security
• Maintainability
• Device Variety
• Operations Criticality
Commercial IoT
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Industrial Automation Mega-Trends
Intelligent
Interactive
Integrated
High-Speed/High-PrecisionReduced Engineering Time
Easier Troubleshooting
①
Flexible & Modular MachinesAutomated ChangeoverReal-time Adjustments
②
Zero Downtime EquipmentPredictive Maintenance
③
Factory IntelligenceCollect, Store & Process Data
Analytics & Improvement
④
Flexible Production LinesConveyor-lessMobile Robots
⑤
Collaborative ProductionCobotics & Safety
⑥
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Finding Value in IIoT
1) Productivity Improvement
2) Quality Improvement
3) Cost Reduction
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1 2 3 4 5
17%8%
67%
8%0%
Poll: What is Your primary IIoT Goal?
1. Cost Reduction
2. Quality Improvement
3. Productivity Improvement
4. Not sure [yet]
5. <N/A>
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3 Main Approaches
Programming SoftwareRuntime Software
Proactive Maintenance
Predictive Maintenance
Line Optimization
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Case 1: Proactive Maintenance
Data storage
Data processing
CloudApps
Manufacturing systems
Sensors
IPC
PLC
Challenges:No capital budgetLimited IT support
Machines
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IO-Link
• Smart Sensors
• Point2Point
• Serial, Bi-directional
• Signal & Energy
• Fast, Reliable
• Automatic Device Configuration
• Plug&Play (Field Replacement)
• IIoT Ready: Connectivity all through ERP
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Case 1 Solution: Smart Sensors
Simplified Installation
Automated parameter setting
Know when a sensor needs maintenance
Productivity+Cost-
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Case 2: Predictive Maintenance
Challenges:No additional HWLimited IT support
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MTBF- Mean Time Between Failure
• Prediction
• Field Reliability
Stable failure rate
Useful Life of Product
Infant Mortality Wear out
Failu
re R
ate
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Case 2 Solution: Integrated Automation
LifeCycle Function Block
Predict when components may fail
Productivity+Cost-
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Case 1.5: Plastic Molding Machine
Reduce downtime: -40%
Tool wear reduction: -20%
Machining sensing +
control system
Force data Feeding speed
commandFeeding speed control
ProactivePredictive
Quality+Productivity+
Cost-
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Case 3: Line Optimization
Multi-function
mounter
High-speed
mounterReflow oven
Solder printing
machine
Vision
inspection
SMT Line
Improve qualityReduce cost
Challenges:Many different machinesUnknown correlationsHigh mix, low volume
Kusatsu
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Case 3: Line Optimization
Multi-function
mounter
High-speed
mounterReflow oven
Solder printing
machine
Server
Vision
inspection
PLC
Machine & Traceability Data
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Copyright: 2017 OMRON Corporation. All Rights Reserved. 18
Visualization at Shanghai Factory
Surface mounting line
Assembly cell line
Data collected by Sysmac NJ
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Copyright: 2017 OMRON Corporation. All Rights Reserved. 19
Process (solder printing, high-speed mounter, multi-function mounter, reflow oven)Tim
e
Movement of
a single PCB
Case 1 “Productivity improvement” PCB mounting line at Visualization
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Copyright: 2017 OMRON Corporation. All Rights Reserved. 20
Case 2 “Productivity improvement” Assembly cell line at Omron Shanghai Factory
Visualization of improvement points in assembly process
Changeover time:
8 min
Changeover time:
11 min
Changeover Optimization
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Copyright: 2017 OMRON Corporation. All Rights Reserved. 21
Cloud
Shanghai Factory
Visualization
Surface mounting line
Assembly cell line
Netherlands Factory
Surface mounting line
Visualization
Surface mounting line
Kusatsu FactoryVisualizatio
n
FA Network Segment
Production Control N/W Segment
Current SMT line in Kusatsu
Global Line Optimization
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Production line
Traceability
Quantities communicated to local networked devices
MES creates order in ERP for low stock
Orders placed, production data communicated to outside parties
Buyer trends communicated to factory, production rates updated
1
2
3
4
5
Automate - Control Internal Processes - Predict Opportunities
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Challenges: Expectations vs. RealityExpectations Reality
Immediate results Iterative process
100% accuracy Improving models
Out-of-the-box Application specific
Leverage current staff New talent required
Use current infrastructure Need additional investments
Full implementation Start small and grow
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Next Steps
1) Decide your IIoT Value
2) Determine what to focus on
3) Investigate what data is available now
4) Consider Technologies / Staff to get & process data
5) Change Management