The manufacturing industry is moving away from just selling machinery, devices, and other hardware. Software and services increase revenue and margins. Equipment-as-a-Service (EaaS) even outsources the maintenance to the vendor. This paradigm shift is only possible with reliable and scalable real-time data processing leveraging an event streaming platform such as Apache Kafka. This talk explores how Kafka-native Condition Monitoring and Predictive Maintenance help with this innovation. More details: https://www.kai-waehner.de/blog/2021/10/25/apache-kafka-condition-monitoring-predictive-maintenance-industrial-iot-digital-twin/ Video recording: https://youtu.be/tfOuN5KeI9w

1. The Rise of Data in Motion
for Industrial IoT and Manufacturing 4.0
Condition Monitoring and Predictive Maintenance in Real-time with Stream Processing
Kai Waehner
Field CTO
kai.waehner@confluent.io
linkedin.com/in/kaiwaehner
confluent.io
kai-waehner.de
@KaiWaehner

2. @KaiWaehner - www.kai-waehner.de - Data in Motion for the Industrial IoT
Real-time Data beats Slow Data.
Manufacturing
Sensor diagnostics
MES/ERP Integration
Reporting
Edge Computing
Condition Monitoring
Predictive
Maintenance
Quality Assurance
Logistics
Supply Chain
Inventory
management
Track & Trace
Context-specific
routing
Cybersecurity
Threat detection
Intrusion detection
Incident response
Fraud detection

3. @KaiWaehner - www.kai-waehner.de - Data in Motion for the Industrial IoT
Industry Trends - Software and Digital Services become the Key Differentiator
3
https://www.mckinsey.com/industries/advanced-electronics/our-insights/iiot-platforms-the-technology-stack-as-value-driver-in-industrial-equipment-and-machinery

4. @KaiWaehner - www.kai-waehner.de - Data in Motion for the Industrial IoT
Apache Kafka is the Platform for Data in Motion
MES
ERP
Sensors
Mobile
Customer 360
Real-time
Alerting System
Data
warehouse
Producers
Consumers
Streams and storage of real time events
Stream
processing
apps
Connectors
Connectors
Stream
processing
apps
Supplier
Alert
Forecast
Inventory Customer
Order
4

5. @KaiWaehner - www.kai-waehner.de - Data in Motion for the Industrial IoT
Shipping Industry
Marine, Oil Transport, Vessel Fleet, Shipping Line, Drones
Real-time Operations, Logistics, Predictive Maintenance, Security
Customer Data
Crew, Cargo
Vessel Data
Fuel Consumption, Speed,
Planned Maintenance
Automatic Identification System (AIS)
Unique Identification,
Position, Course, Weather, Draft
Drone Data
Deliveries,
Survey/Inspection
of Assets such as Oil Rigs,
Pipelines, Offshore Turbines
Edge Analytics
Bidirectional Edge to Cloud Integration
Data Ingestion
Stream
Processing
Data
Integration
Logistics
Track&Trace
Routing
Monitoring
Alerting
Command&Control
Batch Analytics
Reporting
Machine Learning
Backend Systems
Oracle, SAP,
OSIsoft PI, etc.
X = Event Streaming
X = Other Technologies
Bi-Directional Hybrid Cloud
Replication

6. @KaiWaehner - www.kai-waehner.de - Data in Motion for the Industrial IoT
Mercury Systems – Digital Thread
Global technology company serving the aerospace and
defense industry
Digital Thread
• Bring together design and product information across
the product life cycle
• Mendix based portal with combined data from
PLM/ERP/MES
• Confluent for cloud-native and reliable real-time event
streaming across applications
• Apply AI and ML techniques
• All data in one location viewed with common tools
Benefits
• Faster time to market
• Ability to scale
• Improved innovation pipeline and reduced cost of failure
https://www.confluent.io/events/kafka-summit-americas-2021/driving-a-
digital-thread-program-in-manufacturing-with-apache-kafka/

7. @KaiWaehner - www.kai-waehner.de - Data in Motion for the Industrial IoT
Devon Energy
Oil & Gas Industry
Improve drilling and well completion operations
Edge stream processing/analytics + closed-loop control ready
Vendor agnostic (pumping, wireline, coil, offset wells, drilling
operations, producing wells)
Replication to the cloud in real-time at scale
Cloud agnostic (AWS, GCP, Azure)
Source: Energy in Data - Powered by AAPG, SEG & SPE: energyindata.org

8. @KaiWaehner - www.kai-waehner.de - Data in Motion for the Industrial IoT
Severstal – Real-time Shop Floor
Predictive Maintenance and Quality Assurance at the Shop Floor
Real Time Streaming Machine Learning with Kafka

9. @KaiWaehner - www.kai-waehner.de - Data in Motion for the Industrial IoT
Condition Monitoring and Predictive Maintenance
Stateless and stateful stream processing for real-time data correlation with Kafka-native tools (Kafka Streams / ksqlDB)
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Sensor Events

10. @KaiWaehner - www.kai-waehner.de - Data in Motion for the Industrial IoT
Condition Monitoring and Predictive Maintenance
Stateless and stateful stream processing for real-time data correlation with Kafka-native tools (Kafka Streams / ksqlDB)
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Sensor Events
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Condition Monitoring
(Temperature Spikes)
Stateless Filter Above-Threshold Events
Streams
builder
.stream(”temperature-sensor")
.filter((key, sensor-data) ->
sensor-data.temperature > 100)
.to(”temperature-spikes");

11. @KaiWaehner - www.kai-waehner.de - Data in Motion for the Industrial IoT
Condition Monitoring and Predictive Maintenance
Stateless and stateful stream processing for real-time data correlation with Kafka-native tools (Kafka Streams / ksqlDB)
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Sensor Events
Predictive Maintenance
(Continuous Anomaly Detection)
Stateful Correlation of Events
CREATE TABLE anomaly_detection AS
SELECT temperature_spike_id, COUNT(*) AS total_spikes,
AVG(temperature) AS avg_temperature
FROM sensor-data
WINDOW TUMBLING (SIZE 1 HOUR)
GROUP BY temperature_spike_id
EMIT CHANGES;

12. @KaiWaehner - www.kai-waehner.de - Data in Motion for the Industrial IoT
Condition Monitoring and Predictive Maintenance
Stateless and stateful stream processing for real-time data correlation with Kafka-native tools (Kafka Streams / ksqlDB)
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Sensor Events
Predictive Maintenance
(Continuous Anomaly Detection)
Real-time Machine Learning
CREATE STREAM anomaly_detection AS
SELECT sensor_id, detect_anomaly(sensor_values)
FROM machine;
TensorFlow model embedded in User Defined Function (UDF)

13. @KaiWaehner - www.kai-waehner.de - Data in Motion for the Industrial IoT
Condition Monitoring and Predictive Maintenance
Stateless and stateful stream processing for real-time data correlation with Kafka-native tools (Kafka Streams / ksqlDB)
8 9
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Condition Monitoring
(Temperature Spikes)
Time
Predictive Maintenance
(Continuous Anomaly Detection)
Stateful Correlation of Events Stateless Filter Above-Threshold Events
Streams
Sensor Events

14. @KaiWaehner - www.kai-waehner.de - Data in Motion for the Industrial IoT
CRM
Real-Time Location System (RTLS)
for Asset Tracking
Customer data
Advanced Planning
and Scheduling (APS)
Manager
Get report
API
Customer Customer
Customer
data
Truck
schedule
Payment
data
Route
details
Streams of real time events
Customer
data
Train
schedule
Payment
data
Loyalty
information
Streams of real time events
Customer
data
Train
schedule
Payment
data
Loyalty
information
Streams of real time events
Event Streaming in Hybrid Industrial IoT
Wavelength
Public Cloud VPC
Campus 5G Telco Carrier 5G
Smart Factory Edge Computing

15. @KaiWaehner - www.kai-waehner.de - Data in Motion for the Industrial IoT
Car Engine Car Self-driving Car
Confluent completes Apache Kafka. Cloud-native. Everywhere.

16. Kai Waehner
Field CTO
kai.waehner@confluent.io
confluent.io
kai-waehner.de
@KaiWaehner
linkedin.com/in/kaiwaehner
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