AI in Industry

1. AI in Industry
presented by
Dr. Nivine Guler
Informatics Engineering Department
University of Technology Bahrain
Salmabad-Bahrain

2. Table of contents
AI overview
Industrial AI
Influence of AI in
Industry and
Production
Case Studies
Aspects of AI
03 Core Functionalities
02
AI in Market
04
Examples of Industrial AI
01
Future of Industrial AI
05

3. Introduction
Artificial intelligence has been remarked as a
branch of computer science aiming at
transforming a machine or a computer system
into more intelligent systems by imitating the
human capabilities such as reasoning,
acquiring semantic, and learning from past
experience.

4. Aspects of AI
01
AI overview

5. Four aspects of Artificially
Intelligent Software
It should –
● Act humanly -The Turing Test approach
● Think humanly -The cognitive modelling approach
● Think rationally
● Act rationally
The Turing Test, proposed by Alan Turing(1950), was
designed to provide a satisfactory operational definition
of intelligence. Turing defined intelligent behavior as the
ability to achieve human-level performance in all
cognitive tasks, sufficient to fool an interrogator.
Capabilities include –
o Cognitive Science - the study of thought, learning, and
mental organization, which draws on aspects of
psychology, linguistics, philosophy, and computer
modelling
o Natural language processing to enable it to
communicate successfully in English
o Knowledge representation to store information
provided before or during the interrogation
o Automated reasoning to use the stored information to
answer questions and to draw new conclusions;
o Machine learning to adapt to new circumstances and
to detect and extrapolate patterns.
- Thinking with logic
- Always doing the right thing
01
AI overview

6. AI
Act rationally
Always doing the right thing
Think humanly
The cognitive
modelling
approach
Act humanly
The Turing Test approach
Think rationally
Thinking with logic

7. AI in market
02
Infuence of AI
in Industry &
Production

8. 03
AI in market
AI technology has transformed the way machines work and
carry out various tasks, from simple to complicated. Driverless
cars, virtual doctors, smart home appliances, and facial
recognition are all examples of AI-powered machines.
No industry remains untouched by the excellence of AI
technology. In fact, the market range of products integrated
with AI is expected to hit $ 140 Billion by 2030.
The impact of AI has been depicted in many fields, like
science in cancer research, toxicology; automotive in self-
driving solutions, easy navigation and identifying defects in-car
components; and in education as predictive algorithms and
building personalized learning plans.

9. o The purpose of AI is to automate tasks more accurately and
quickly than if done by a person.
o Companies like Amazon and Netflix use AI to provide their
customers with recommendations based on what other people
have purchased or what people who like “X” genre of shows
watched next.
02
AI in market

10. 02 o Small businesses like travel companies
provide their customers with
recommendations about specific
details of their trip or predictions about
their projected plans via machine
learning (ML).
o In field of Data analysis, acquiring,
filtering, sorting, and analyzing data
takes a lot of time by data analyst;
hence, ML algorithms powered by AI
help automate the difficult task of data
analysis.
02
AI in market

11. 02
AI in market
Global AI Market
 More than 80% of companies expect to use intelligent automation
in retail and consumer products by 2025.
 They believe this technology could help increase their annual
revenue by 10% where 28% of companies use AI in their
marketing efforts. In addition, 31% plan to begin using it within the
year

12. 02
AI in market
Benefits
of AI
Improve AI
ethics,
explainability,
and bias
detection
Help
employees
make better
decisions
Analyze
scenarios
using
simulation
modeling
Automate
routine tasks

13. oHealthcare and medicine
oEducation
oMarketing
oIndustry
oRetail and e-commerce
oPublic relations (PR)
oRecruitment and human resources (HR)
Most 7 industries depending on AI
02
AI in market

14. 02
AI in amrket
AI in Healthcare sector
The AI industry provides the necessary tools for disease diagnosis,
prevention, and tracking & monitoring.
o Electronic health records (EHR), Tracking Devices
A very widely discussed and successful example of an AI healthcare
application is the treatment of Alzheimer’s disease. It was
demonstrated by the ease of accessibility of a home assistance device,
namely the Amazon Echo Dot.
The AI gadget turns out to be an effective tool for patients with
Alzheimer’s as it provides notifications and messages reminding them
about medications, greatly improving their health.

16. 02
AI in market
AI in Agriculture
These days, there has been a rise of several mobile apps accessible to
agriculture businesses that help in detailing the weather conditions,
soil toxicity levels, temperature, etc.
This data collected over some time is important in analyzing the right
time for sowing and plant growth. It helps understand and provide
insights to determine the best conditions to obtain a bountiful
harvest.
The use of AI sensors helps target weeds and other invasive pests to
control the damage. It also aids in determining the content of
herbicides used and suggests a cost-effective and green solution for
it.

17. 02
AI in market
AI in Education
 Revolutionizing the education industry directly impacts the
generation to become smarter. Hence, transforming education is on
the premises of AI companies to built intelligent apps.
 In education, there’s a huge demand for mobile app development
solutions to build safe and secure apps for children that enhance
their social skills; e.g. Quizlet

18. 02
AI in market
AI in Marketing
 AI technology is the game-changer for the marketing sector.
From creating personalized advertising content to making
purchase suggestions based on the previous purchase, AI is
revolutionizing user experience and transforming the way
people purchase products and businesses sell them.
 AI is a versatile tool for marketing, capable of handling a wide
range of routine-based tasks quickly and accurately such as
sending sales emails, creating customer profiles, and managing
sales data

19. 02
AI in market
Companies that adopted AI
Netflix provides personalizing recommendations to its 100 million
subscribers worldwide, improving search results and avoiding
canceled subscriptions
Bloomberg uses AI techniques to improve the breadth of
information that financial staffs use to access market information.
Uber uses AI to better predict traveling habits and improve maps
using computer vision, and to create algorithms for its autonomous
vehicles.
Royal Bank of Scotland uses natural language processing AI bot
that answers customer questions and performs money transfers.

20. Details of core functionalities
03
Industrial AI

21. 03
Industrial AI
Industrial AI refers to the application of artificial intelligence to
industry which is concerned with applications of smart
technologies that mimic human intelligence to address industrial
backbone for customer value creation, productivity improvement,
cost reduction, site optimization, predictive analysis.

23. Collaborative robotic arms able to learn
the motion and path demonstrated by
human operators and perform the same
task.

24. The Machine Learning Pipeline in Production is a domain-specific data science methodology, inspired by
the CRISP-DM model, and was specifically designed to be applied in fields of engineering and production
technology.
To address the core challenges of ML in engineering, the methodology especially focuses on use-case
assessment, achieving a common data and process understanding data integration, data preprocessing
of real-world production data and the deployment and certification of real-world ML applications.

25. Future begins with AI
04
Future of
Industrial AI

26. 04
Future of AI
Industrial digital transformation is critical to achieving new levels
of safety, sustainability, and profitability—and “Industrial AI” is a
key enabler of that change.
Today’s industrial organizations aim at reinforcing their industrial
operations and complex value chains with greater resiliency and
flexibility to respond to shifting market conditions.
At the same time, they’re investing in autonomous and semi-
autonomous artificial intelligence (AI) capabilities to realize their
vision of the digital plant of the future—the “Self-Optimizing Plant.”

28. Examples of Industrial AI
05
Case Studies

29. 05
Case 1
Using synthetic data to pick and place different objects with robots
An NVIDIA customer, Soft Robotics, for instance, worked with a food
producer to create an AI solution that enables a robot to recognize and
pick up single, wet and squishy chicken wings out of a pile of wings.
Where does one wing start and end, though? And what’s the best way
to grip a specific wing?
It’s a challenging task. A pile of chicken wings can form an infinite
number of positions or poses.
Solution?
Rather than taking 10,000 pictures of all the ways chicken parts randomly drop,
AI can build photorealistic, physically accurate 3D representations and put
them under different lighting conditions.
Using the images from the simulation to train the AI model saves time
compared with photographing and labeling thousands of real-world images.

30. 05
Case 2
Using outlier cycle detection to double the throughput of a production line
A Tier 2 automotive supplier, for instance, doubled the throughput of a
production line with Invisible AI’s help.
Using AI tools, they identified high spikes in cycle times at some stations,
including the workstation shown in the shift management workflow chart.

31. 05
Case 3
Predictive maintenance is one of the first things to implement with AI in
an industrial setting. Mechanical parts like bearings wear out that must be
replaced routinely, like changing the engine oil in a car based on distance
traveled.
AI predicts that Machine A is going to fail with a stated confidence level in
the next two days for example, so the maintenance team knows WHICH
BEARINGS to replace before they get stuck. A short, planned
maintenance shutdown results in lossless of production than an
extended, unplanned outage.
Siemens, for instance, used a wealth of production data to increase
throughput of a production line of printed circuit boards by performing 30
percent fewer x-ray tests. They accomplished this task using AI to identify
which boards were likely to benefit from inspection.

32. 05
Case 4
Simulate new factories and processes with agility
New factory design and process changes involve risks that can be
reduced through a 3D simulation in a type of virtual factory, otherwise
known as a digital twin.
Linked to existing systems, a digital twin looks and works like the real-
world factory
Siemens, for instance, used a wealth of production data to increase
throughput
A FREYR virtual battery factory, for instance, provides 3D
representations of the infrastructure, plant, machinery, equipment, human
ergonomics, safety information, robots, automated guided vehicles, and
detailed product and production simulations.
A digital twin of a BMW automotive factory is another example. With
simulation, the entire planning phase of the manufacturing facility can
happen in a virtual world, and everything can be tried out and tested.

34. —N. Guler
“Industrial AI is not about replacing humans, but about
augmenting human capabilities, enabling us to achieve new levels
of productivity, efficiency, and safety in the workplace.”