1. The document discusses IBM's strategy around cognitive manufacturing and the Industrial Internet of Things (IIoT). 2. It describes IBM's Watson IoT platform, which collects data from devices, enables edge analytics, and provides analytics and cognitive capabilities to help manufacturers predict needs, improve decision making, and gain competitive advantages. 3. Examples are given of how IBM has helped manufacturers increase productivity, reduce costs, and improve quality through applying cognitive technologies like predictive analytics, machine learning and natural language processing to manufacturing data.

1. 1
From Industrie 4.0 to
Cognitive Manufacturing
Thorsten Schröer
Director and Industry Leader
Watson IoT for Manufacturing
www.localmotors.com

2. 2
Our strategy
+ +

3. 3
Analytics
Customer
Engagement Security
Powered by CognitiveIndustry Specialization
Healthcare Finance IoT
Global
Ecosystem
Content ConversationComputeCloud
Watson Platform
Data (Public, Private, Partner)
Built cloud-based industry platform

4. 4
BlockchainEdgeWeather
Predict need and improve
decision making
Analyze data and act on it close
to the source
Share transactions with tamper-resistant
records, transparency and trust
IoT Devices
IBM Watson IoT Platform,
Business Analytics
and Cognition
Cisco Edge
& Edge Analytics
Equipping you with competitive advantage and game-changing technology

5. 5
Eco-System Extending capabilities with
partners
IBM IoT for
Electronics
IBM IoT for
Automotive
2015 2016
IBM Bluemix
IoT Zone
Maximo for
aviation
Maximo Asset
Management
TRIRIGA Data
Manager
Maximo for Oil and Gas,
Service Providers,
Health/Safety/Env
Platform
partners
Device and
network partners
Application
partners
Industry solution
partners
IBM IoT for
Manufacturing

6. 6

7. 7
The Analyst view
Source: Forrester wave– iot software platforms 4q 2016 (November 2016) Source: Gartner Magic Quadrant for Data Science Platforms

8. 8

9. 9
Artificial Intelligence - IBM Watson

10. 10>1890 Tabulating 1960 Programmable >2010 Cognitive

11. A Cognitive Solution =
Analytical
System
Natural Language Processing
(NLP)
Machine Learning/
Deep Learning
+
+

12. Why Cognitive
in Manufacturing and Supply Chain?

13. Cognitive Manufacturing – Stairway to heaven
Gather the
data
Visualize the
patterns
Advance to
analytics
Infuse with
cognitive
• Instrument your
equipment/assets to
collect data
• Gather already
existing data
• Visualize your data
in meaningful
dashboards
• Start to see patterns
• Gain insights from
the data
• Produce models,
prediction
recommendations
• Enrich with data
from other sources
• Refine models with
cognitive machine
learning
• Utilize other
cognitive functions
to improve
engagement
Asset needs to
be connected,
outfitted with
sensor or data
gathered
Use analytical
models to predict
equipment failures
and provide
recommendations
Use the
platform to
quickly build
dashboards for
data
visualization
Use speech,
video, image
to diagnose
complex
problems

14. IBM Watson IoT for Manufacturing

15. 15
For analytics, utilize purpose driven advanced analytics dedicated to
manufacturing metrics or generate your own models with PMQ
IBM Watson IoT for Manufacturing
Manufacturing Analytics PMQ
Plant
Performance
Analytics
Maintenance
Analytics
Quality
Analytics
Warranty
Analytics
• Prebuilt industry models
• Role specific user interface
• Proven algorithms
• Cognitive extension (future)
• Packaged
analytics tools
• Custom build
and execute
models
• BI customizable
interface

16. 16
IBM Prescriptive Quality on Cloud
Earlier, more definitive detection of quality problems in
comparison to traditional statistical process control methods.
Reduce scrap and re-work
Improve process throughput
Lower supply and material costs
Increase production yield
ibm.co/pqoncloud-trial

17. 17
Differentiating elements of Watson IoT technology and ecosystem
Partnered
Innovation
Open ecosystem
Device partnerships
Embedded security
Edge Analytics
Data
Integration
Weather data
Social data
Application data
Platform of platforms
Advanced
Analytics
Predictive Analytics
Real-time Analytics
Data Mining
Optimization
Cognitive
Technology
Natural Language Processing
Machine Learning
Textual Analytics
Video/Image Analytics

18. 18
Cognitive Visual Inspector
Cognitive Equipment Advisor
Cognitive Robotics
Cognitive Acoustic Inspector
Cognitive Energy Optimizer
Cognitive Quality Analyzer
Cognitive Planner
Cognitive Resolution Room
Cognitive Supply Chain Advisor
Cognitive Plant Advisor

20. Project Examples

21. 21
SmartFactoryKL Demonstrator 2015
Fast setup and change of manufacturing lines
Lotsize 1 with +ROI
+ROI in high labour country
Provides and organizes the partner network
www.smartfactory-kl.de
I4.0 – Smart Factory

22. IBM helped an automotive
manufacturer gain a far
deeper understanding of the
many factors that affect
production quality
25% increase
in the overall productivity of the cylinder-head
production line
100% payback
achieved within two years
50% reduction
in the time required to ramp up the process
to target levels

23. Industrie 4.0 & Cognitive Factory at John Deere Mannheim
Worker Assistance

24. Watson IoT Platform
Cognitive Robot Demo
Machine
learning Text
Image
Natural
Language
Watson Cognitive
Analytics
Foxbot writes
calligraphyHannover Messe 2016
Voice
recognition

25. Dashboard shows
KPI information
Foxbot publishes
joint sensor data
IBM PMQ observes operational statistics,
raises maintenance notifications
MQTT
Conversation with operations
manager using Bluetooth headset
1 2 3
4
Cognitive robot maintenance example
Watson IoT
Platform
PMQ
Bluemix
Watson
conversation & voice
services

26. Images
images captured using
Imaging Station in production
11
Defects cross- checked
against library of past images
and trained algorithms for reuse
12
Reuse previously trained
algorithms and retrain in
production to handle variations
3a
Develop new image
analytics and train over sample
sets to have high accuracy; Deploy
to production as a new base case
1
3b
Variation
of past
case?
Entirely
new
case?
Connects &
Reasons
Real Time Monitor
Learning System
Machine Learning system
crawls through library and
attempts to improve algorithm
accuracy over larger data set.
5
PMQ Analytics and
reporting for daily, weekly, per
shift reports
14
COGNITIVE VISUAL INSPECTOR

27. 27
Cognitive Quality Advisor
Cognitive Supply Chain Disruptions Advisor
Cognitive Resolution Rooms Advisor
We teach Watson Supply Chain.
IBM Supply Chain Operations Group drives to become a cognitive business

28. 28
ibm.biz/cogmanufacture

29. 29
IBM’s commitment to the Internet of Things

30. 30
Collabratory Clients

31. 31
IBM Watson IoT Center

32. Final thought
“The biggest danger to a producer with a factory is a
producer without a factory.”
Prof. Dr. Günther Schuh, RWTH Aachen