EXPERIMENT NO.
– 1
AIM: - One case study on AI applications published in IEEE/ACM/Springer or any prominent journal.
THEORY: -
Artificial Intelligence in Automation
ABSTRACT
The development of Artificial Intelligence is speeding up rapidly and combination ofArtificial
Intelligence with automation has started to change the business landscape. Companies
and business are focusing on applying existing Artificial Intelligence withautomation
processes to gain the new heights of efficiency and quality.
INTRODUCTION
Artificial Intelligence (AI) is the science that enables the computers and the machines to learn, judge
and use own reasons. As the technologies are becoming more complex, the demand of Artificial
Intelligence is growing because of its ability to solve complex problems with limited human
resources and expertise and within a limited time. There is a big breakthrough in the field of image
recognition using machine learning along with the advances in big data and GPU (Graphic processing
units) which evidently helped Artificial Intelligence grow faster.
Artificial Intelligence (AI) system consists of an agent and its environment. An agent such as human
or a robot identifies the environment through sensors and effectors. It uses a method called search
and pattern matching where the computer is instructed to search its knowledgebase based on the
match found and if specific conditions are met to solve a problem.
CONCEPT OF AUTOMATION
The use of automation began to increase in the last decade with an aim to reduce manpower and
time. Automation has introduced a system of computer and machines andreplaced a system that
was built by combining man and machine. Highly intense and repetitive tasks have become
efficient and the product quality has also increased with the useautomation in various industries.
There are various types of automation, some of the popular ones are as follows: -
2.1 Numerical Control
3D printing, glass cutting, etc. fall in this category where machines are programmed toexecute
repetitive tasks.
2.2 Computer-aided manufacturing (CAM)
Computer software are used for this automation example of which are like Computer-aided design
(CAD), Computer -aided design and drafting etc.
2.3 Flexible manufacturing systems (FMS)
It is a sophisticated automation system where robots and other advanced automation tools are
used to provide flexibility and customization to the users.
2.4 Industrial robot:
Robots are being used for welding, assembly and handling materials etc. where robots can be
programmed and manipulated in three or more axes.
What Are the Major Components of AI in Automation?
An automation system functions using the three components of artificial intelligence. So, depending
on the need, they can be either combined or even used separately to allow for a fully automated
response:
Machine Vision: This refers to the potential of any program to understand what the visual input is.
The machine makes use of the training data (images) as a type of foundationfor the identification or
classification mechanism. For example, face recognition system of iPhone X uses machine vison
technology.
Natural Language Processing: Machine language world on the visuals, Natural Language
Processing (NLP) does the same to understand human voice and text inputs. It'snow possible for
machines to understand what the context behind the communication is being carried out and then
take actions based on the kind of prebuilt data and contextual variableswhich are at play. Some
examples of this are Apple's Siri, Amazon Alexa and such.
Machine Learning: It refers to the ability of a machine to learn using the data fed to it. This involves
the outcomes of environment variables and decisions to improve itself. Usingmachine learning we
will be able to improve the total efficiency of current solutions.
What Are the Important Applications of Artificial Intelligence in Automation?
Artificial Intelligence (AI) plays a crucial role in automation across various industries, enhancing
efficiency, decision-making, and adaptability. Here are some important applications of AI in
automation:
1. Predictive Maintenance:
AI algorithms analyze historical data and sensor information to predict when
equipment is likely to fail.
Predictive maintenance reduces downtime and increases the lifespan of machinery
by allowing for timely repairs or replacements.
2. Robotic Process Automation (RPA):
AI-powered robots and bots automate repetitive and rule-based tasks.
RPA is used in industries such as manufacturing, finance, and healthcare to
streamline processes and improve accuracy.
3. Supply Chain Optimization:
AI aids in optimizing supply chain processes by predicting demand, managing
inventory, and optimizing logistics.
Machine learning algorithms analyze historical data to identify patterns and trends,
facilitating better decision-making in supply chain management.
4. Smart Manufacturing:
AI is used to create intelligent and adaptive manufacturing systems.
Automation in manufacturing benefits from AI-driven technologies like computer
vision, predictive analytics, and machine learning for quality control, production
optimization, and resource management.
5. Quality Control:
AI-powered systems inspect and assess product quality during manufacturing
processes.
Computer vision and machine learning algorithms identify defects or anomalies,
ensuring high-quality production.
6. Autonomous Vehicles:
AI is a key technology in the development of autonomous vehicles, including self-
driving cars, trucks, and drones.
Machine learning algorithms process data from sensors, cameras, and other sources
to make real-time decisions for navigation and obstacle avoidance.
Intelligence’s learning ability, efficiency increases over time. Even though, there is a good
advancement in the field of Automation and Artificial Intelligence, both Artificial
Intelligence and machine learning are yet to be optimized. Companies have realized that
the key to the business success is subjected to machine learning, artificial intelligence and
automation. Soon, the companies will be fully equipped with these start systems and would
completely change the traditional systems with by yielding significant benefits.
CONCLUSION: Hence, we have successfully done Case Study on AI Application
