A look at how cognitive computing is driving new productivity and gains in the manufacturing industry. TO learn more: http://www.ibm.com/internet-of-things/iot-solutions/connected-manufacturing/

1. Journey to Industry 4.0
and beyond with
Cognitive Manufacturing

2. 2
We’re entering the fourth revolution of industry and it is fully differentiated
from any that came before it
Line
Production
Electrification &
Automation
Miniaturization &
Global Scale
Cognitive
Manufacturing
Complexity
Era
1783
1870
1960
2020
Water, steam, and
conveyors; modern
materials handling
Assembly systems:
Lighting, electricity
and assembly lines
Embedded
systems:
Semiconductors,
computers,
information
technologies and
increase in trade
Cyber-physical
systems: sensors,
big data, predictive
analytics, cognitive
computing, cyber-
physical systems,
robotics, 3D
printing

3. 3
collected manufacturing
and enterprise data
Smarter
Supply Chain
Management
Smarter
Energy
Smarter
Factory
Operations
Smarter
Product
Design
Smarter
Employee
Safety
Smarter
Quality
made into a transparent,
comprehensive,
interactive, minable corpus
of information
that makes visible new
patterns in the data
to continuously monitor,
predict, respond and
interact with humans and
machines
To deliver
Smarter
Equipment
Maintenance
Cognitive Manufacturing applies cognitive capabilities to digitize and
optimize previously inaccessible areas of manufacturing processes

4. 4
To capture the potential of the cognitive manufacturing transformation,
we focus on three key pillars of manufacturing that drive the highest
improvement
Intelligent
Asset and
Equipment
Smarter
Resources and
Optimization
Cognitive
Process and
Operations

5. 5
Intelligent Assets and Equipment
Intelligent assets and equipment utilizes IoT and cognitive capabilities to
sense, communicate and self-diagnose issues so they can optimize their
performance and reduce unnecessary downtime
 Prevent production delays and improve line
performance with better asset visibility
 Reduce equipment downtime and increase
process efficiency with industry models
 Expedite equipment repairs through
predictive and cognitive analytics
Decrease in equipment
downtime at major
global auto manufacturer
34%

6. 6
Auto manufacturers are utilizing the
analytics capabilities of Watson IoT
combined with new sources of real-time
data to gain new predictions and
prescription on improving equipment
availability and performance. Using prebuilt
industry models, manufacturer can spend
less to analyzing and more time doing.

7. 7
Equipment downtime can be significantly
reduced by combining the power of IoT
with cognitive capability. Not only can
Watson IoT predict what and when failures
can happen, it can utilize cognitive
capabilities to advise a user on exactly how
to fix and resolve these failures.

8. 8
Cognitive Process and Operations
Cognitive operations and processes bring more certainty to business by
analyzing a variety of information from workflows, context and environment to
drive quality, enhance operations and decision-making.
 Increase yield of your manufacturing
operations and processes
 Improve productivity of your manufacturing
line with early quality detection
 Expedite service calls and repairs and reduce
warranty costs
Increase in overall
productivity at major
European automaker
25%

9. 9
With quality analytics from Watson IoT
manufacturers can analyze hundreds of
process variables, historic and real-time, to
identify issues contributing to quality issues
and resolve them before they occur. This
drastically improves productivity and yield
while reducing operation and material
costs.

10. 10
By utilizing cognitive capabilities, Watson
IoT can bring in unstructured data such as
image and video which enriches the
information around manufacturing
processes. Combined with other IoT data,
this information can produce more
accurate predictions and better insights

11. 11
Smarter Resource and Optimization
Utilize IoT and cognitive insight to optimize the resources engaged around
production, whether that’s keeping production line workers safe, improving the
expertise of the entire workforce or optimizing energy consumption
 Improve worker safety and gain better
workforce management
 Increase worker productivity and expertise
 Reduce energy consumption of your facilities
and buildings
Reduced energy and
resource costs at
manufacturing facility by
8%

12. 12
Industrial manufacturers are using Watson
IoT to help employees stay safer in
dangerous environments. The solution
detects hazardous environments and
provides real-time alerts to employees and
employers enabling preventive measures if
physical well-being is compromised or
safety procedures have not been applied.

13. 13
Engineers are training Watson to collate
30+ years of engineering experience in
managing liquid gas facilities to create a
cognitive advisory service to help
employees across the organization resolve
problems faster, improve process flow and
achieve better operational outcomes.

14. 14
Embracing cognitive manufacturing
Collect the
Data
Collect and curate the
right data— data on
processes and
operations you would like
to improve, data across
your systems, both
structured and
unstructured. Connect
systems and sensors to
bring in real-time data for
more accurate insights
Visualize the
Patterns
Visualize your data on a
platform. Quickly build up
dashboards and use
simple analytics to
determine patterns.
Supplement with external
sources of data and
analyze variables that
impact the process and
operation you would like
to improve.
Analyze with
Purpose
Apply purpose driven
analytics to gain new
insights from you data
Developed advanced
models, process a
combination of variables
and utilize the prediction
engine to generate the
best recommendations
the drive the most
business results
Deliver with
Cognitive
Whether it’s dealing with
vast amounts of IoT data
or dark and unstructured
data, cognitive
capabilities brings light
and clarity. Take
advantage of the
processing power of
cognitive to enable you to
act, resolve, and deliver
better

15. 15
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