The document discusses how AWS can help manufacturers with their digital transformation and Industry 4.0 initiatives. It outlines how AWS enables smart factories and smart products through connectivity, sensors, cloud computing, analytics and AI. This allows for increased efficiency, data-driven decision making, and products that improve over time. The document also provides an example of how AWS technologies like IoT, machine learning and analytics can help optimize manufacturing operations and meet business goals. Finally, it presents an AWS reference architecture for integrating manufacturing systems with the cloud.
4. Industry 4.0
4
Autonomous
Robots
Simulation & HPC
Vertical & Horizontal
Integration
Industrial Internet of
Things
Cybersecurity
Cloud
Additive
Manufacturing
Augmented
Reality
Big Data
ML, Analytics
Technical enablersCommon use cases
• Smart Factory
• Smart Products & Services
• ML driven Quality Control
• ML based forecasting
• ML based planning
• Self driving logistics vehicles
• Digital Twin
• Smart Supply chains
• Predictive Maintenance
• Self organizing production
• Disaster recovery
• SAP on AWS
• Knowledge Transfer of maintenance/service staff
9. Manufacturing Operations Business Matrix
Plant Manager Quality Manager H&S Officer Production
Planner
Plant
Maintenance
Performance
Quality
Availability
Safety
Product
Increase/Optimize
Production line
throughput
Optimize Production
Line throughput
Optimize Asset
Lifecycle
Reduce
Scrap/Defects
Reduce
Scrap/Defects
Reduce unplanned
outages / stoppages
No unplanned
outages
Zero safety incidents
Increase Quality
Build to Order
Optimize Supply
Chain
Build to Order
Minimize Stock
Production
Manager
Protect workforce
Safe Environment
Asset Maintenance
Track Inventory
Reduce Rework
Build to Plan
Engineer
Reduce
Engineering
Change Orders
Reduce Design
Time
Enable safe work
environment
Representative
10. Envisioning Example
Business Outcomes / Goals
Enabling
Technologies Stakeholders
Increase Performance
Increase Quality
Plant Manager
Production
Planner
Quality Manager
Plant Manager
Metrics
Increase Availability
Line Utilization
M O
Stoppage Time
M O
% of rework
M O
M O
Optimized
Production
Throughput
Implement JiT
Inventory
No unplanned
downtime
Reduce rework
Production Planning
Forecasting ML
Data Lake
Deep Learning
Video Defect
Detection
Analytics for
Predictive
Maintenance
11. ISA-95 triangle in the context of the AWS Cloud
Level 1
Level 2
Line/Machine
Control
Animation
Direct Control
Level 3
Level 4
Description
Line/Machine
Supervision
Manufacturing
Operations
Management
Business
Planning &
Logistics
MES/
Historian
ERP/PLP/SCM
App/SystemFunction
Line/Cell
Execution
Business
Operations
SCADA/HMI
Supervisory
Control
DCS/PLC/RTU
Level 0
Physical
Values
Raw Data
Event Signals
I/O Sensor
AWS
Architecture
Enterprise
Apps in the
Cloud
Data
Ingestion &
Analytics
Edge /
Greengrass
IoT Device