The Industrial Revolution began in the United Kingdom in the late 18th century.

Steam engines were the primary source of power during the early stages of the Industrial Revolution.

The spinning jenny was invented by James Hargreaves in 1764 and revolutionized the textile industry by enabling multiple threads to be spun simultaneously.

Adam Smith is considered the father of modern economics due to his groundbreaking work, 'The Wealth of Nations', published in 1776.

Luddism was a social and political movement that emerged in the early 19th century in response to the negative effects of the Industrial Revolution, particularly the displacement of workers due to automation.

The assembly line, pioneered by Henry Ford in the early 20th century, enabled mass production of automobiles by breaking down the manufacturing process into smaller, repetitive tasks.

COBOL (Common Business-Oriented Language) was developed by Grace Hopper in the 1950s and was specifically designed for business applications.

The development of the microprocessor in the 1970s led to the creation of personal computers, making computing accessible to individuals and small businesses.

Industry 4.0 is the term used to describe the current trend of automation and technology integration in industries, leading to increased efficiency and productivity.

The Internet of Things (IoT) is often associated with smart factories, as it enables the interconnection of various devices and sensors to collect and exchange data, leading to improved automation and efficiency.

The primary goal of automation in industrial settings is to increase productivity by streamlining processes, reducing manual labor, and optimizing resource utilization.

Cartesian robots, also known as gantry robots, are commonly used in assembly lines for repetitive tasks due to their precise movement along linear axes.

Cyber-physical systems (CPS) is the term used to describe the integration of physical and digital systems in manufacturing processes, enabling real-time monitoring, control, and optimization.

Machine learning (ML) algorithms are often used for predictive maintenance in automated systems by analyzing historical data to identify potential failures and schedule maintenance accordingly.

Human-robot collaboration (HRC) is the term used to describe the seamless collaboration between humans and robots in industrial settings, where robots assist humans in various tasks.