Industry 4.0
Infographic History
Nowadays, terms like Internet of Things, Big Data, Data Analytics, Artificial Intelligence, Virtual Reality, Augmented Reality and other elements of the so called Industry 4.0 or Fourth Industrial Revolution are commonly discussed in our daily lives. So, are these tendencies the future or are they our present? The fact is the Industry 4.0 is not a utopia anymore, as many facilities from all over the world are already applying it. As its name suggests, the fourth industrial revolution has been preceded by other three.

The first one, in 1784, was caused by the invention of the steam engine and the impact it had over several economic areas, mainly transportation and industrial processes. This huge novelty served as a link between the traditional production system, which involved high costs, waste of raw materials and long waiting times , and mechanized production, which reduced by a large margin all the inconveniences mentioned above.

Then, around 1870, a second revolution began, impulsed by the discovery of the laws governing the electric phenomena. This promoted new manufacturing methods and bigger assembly lines, leading to the emergence of the mass production system. The Ford T model, first produced in 1903, became an icon of this new era, a perfect example of how electricity completely changed sectors like the automotive industry.

About sixty years later, computers arise as main protagonists of the third revolution. Advancements in fields like Internet, robotics and communication networking started to appear at a seemingly constant rate. But it was not until the fourth revolution when Internet-based inventions began to expand in an exponential way.

The basic concept behind the revolution we are living is the transformation from point-to-point connections, established between a single server and a single client computer, to a multi-layered network reaching thousands of electronic device, all of them sending real-time data at all times. This huge structure opens the necessity for interpretative systems, able to analyze millions of data bits and transform them into readable, relevant information for people and organizations.
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