Data are driving the world today and they are becoming world's precious currency. Continuous Engineering, the default set of applications for enterprise software development, produce a wealth of data but it is hard to understand its value. What if you could find hidden patterns in your data your development teams create? What if you could discover ways to improve your team's performance? This presentation reviewed some of the different ways the Collaborative Lifecycle Management team (http://jazz.net) is utilizing Watson Analytics to gain insights into and improve efficiency with their own processes.

1. Cognitive Digital Twin
Fariz Saracevic, IBM, Senior Offering Manager
HOTEL EUROPE, October 21st

3. IBM Confidential – Shared under NDA3
• What is cognitive/artificial intelligence?
• Industry disruption and big data
• Why cognitive engineering
• Cognitive engineering scenarios
– Watson Analytics and Cognitive Quality Advisor
– Cognitive Requirements Advisor
– Cognitive Modeling Advisor
• Demo
Outline

4. IBM Confidential – Shared under NDA4
Is it Science? Is it Technology?
Is it Magic?
What is Cognitive/Artificial Intelligence?

5. IBM Confidential – Shared under NDA5
• Cognitive computing (CC) describes technology platforms that, broadly speaking, are
based on the scientific disciplines of artificial intelligence and signal processing. These
platforms encompass machine learning, reasoning, natural language
processing, speech recognition and vision (object recognition), human–computer
interaction, dialog and narrative generation, among other technologies.[1][2]
• Artificial intelligence (AI, also machine intelligence, MI) is
apparently intelligent behaviour by machines, rather than the natural intelligence (NI) of
humans and other animals. In computer science AI research is defined as the study of
"intelligent agents": any device that perceives its environment and takes actions that
maximize its chance of success at some goal.[1] Colloquially, the term "artificial intelligence"
is applied when a machine mimics "cognitive" functions that humans associate with
other human minds, such as "learning" and "problem solving".[2]
Wikipedia Definitions

6. IBM Confidential – Shared under NDA6
What is Cognitive/Artificial Intelligence?
Cognitive/Artificial Intelligence is a Science that
uses Technology to Create Magic

7. IBM Confidential – Shared under NDA7
We are going through an era of disruption

8. IBM Confidential – Shared under NDA8
Dramatic technology forces and big data
are behind the “creative disruption”
Digital commerce Cloud
The sharing economy
Mobile
IoT Blockchain
Cognitive AI
Machine
learning
Data is the currency of
the future
Old intermediaries
no longer needed
Explosion of dataPervasive
Interconnectivity
34B connected devices
in 2020
180 Zettabytes in 2025

9. IBM Confidential – Shared under NDA9
Data is the currency of the future

10. 10
Digital twin: getting a clear view
new user experience
cognitive analytics
digital threads
cognitive sensing

11. Cognitive Digital Twin: Blending Digital and Physical Worlds
Cognitive digital twin:
A virtual representation of a physical object or system across its lifecycle (design, build, operate)
using real time data from IoT sensors and other sources
to enable learning, reasoning and automatically adjusting for improved decision making.
Build
Design
Operate
A comprehensive set of capabilities and
information models
 Enable shorter design cycle and speed
up innovation
 Support change management and
solution impact analysis
• Provide tight linkage between design,
build, and operate
• Optimize asset operation & performance
• Leverage operational insights back to
design
Better understanding of
design for rapid
development
Increased transparency
for more efficient
manufacturing
Empowered decision making for
optimized operation

12. Cognitive Digital Twin: Leveraging cognitive analytics
Build
Design
Operate
Cognitive Analytics
Analytic Insights

13. IBM Confidential – Shared under NDA13
Cognitive Engineering Journey
Connect & Configure
Monitor & Visualize
Analyze & Predict
Become Cognitive
• Instrument your assets
to collect data
• Connect data sources
• Collect, aggregate &
explore
• Monitor data &
automate actions
• Visualize in
dashboards
• Cross site, cross fleet
• Gain insights from the
data
• Produce models,
predict outcomes, &
make
recommendations
• Bring in cognitive
components
• Unstructured data
• Machine learning
• Cognitive processing

14. IBM Confidential – Shared under NDA14
Our focus areas for cognitive
Continuous Engineering
Cognitive Analytics
Manage
Requirements
Manage
Development
Build and
Deploy
OperateAnalyze
Design for
Analytics
Analytics
for Design
Design
System
Verify and
Validate
Design and DeliverDesign and develop products/solutions
Analyze data to inform
Business Leaders,
Engineers
and Developers
IoT-enabled
products/systems

15. IBM Confidential – Shared under NDA15
Fully Automated
Intelligence
Natural Language
Dialogue
Guided Analytic
Discovery
Single Analytics
Experience
Advanced IBM invention that provides powerful, easy-to-use, self-service
analytics capabilities in the cloud
IBM Watson Analytics Overview

16. Semantic Aware requirements
 Operational data used as inputs for Requirements
analysis/elicitation
 Requirements Quality Assessment
 Detect similar and/or duplicate requirements
 Automated lifecycle transition from requirements to design
 Model Based Systems Engineering
Operations
Manufacturing
Engineering
Requirements

17. IBM Confidential – Shared under NDA17
Cognitive Requirements Advisor
Display
assessment
score based
upon presence
of valued
entities and
relationships
By pressing on the
“Tell Me Why?”
button the user can
begin a chat with
the tool to
understand the
score received and
what to do to
improve it.
By pressing on
the “Score All”
button, the user
can score the
entire module.

18. IBM Confidential – Shared under NDA18
Cognitive Modelling Advisor
Key Benefits
• Turn a 100 page document into a starting point
engineering model in a few minutes using
Watson… this can be up to 100 times faster
• Capture essential aspects of long and
complicated documents very quickly
• Improve requirement quality and structure
Prerequisites
 Watson document converter
 Watson Natural Language Understanding API
 Rhapsody API to populate UPDM model
 Rhapsody Visualizer
Working to make this available as a service
engagement offering

19. IBM Confidential – Shared under NDA19
Cognitive Quality Advisor Overview
•Analyze tests which find
defects or don’t find defects
•Identify tests which should
be run more frequently, or
retired
•Maximize benefits; Find
more “code change” defects
•Minimize overhead;
Eliminate or restructure low
value tests
•Leads to cost savings for
customers

20. IBM Confidential – Shared under NDA20
Demos
Cognitive Quality Advisor
Cognitive Requirements Advisor
Cognitive Modelling Advisor
Contact Names
Fariz Saracevic, Senior Offering Manager, fariz@us.ibm.com
Find more information

21. THANK YOU!