Industry 4.0: definition and implementation to the connected factory
Driven by the emergence of new technologies, Industry 4.0 refers to a new generation of connected, robotic and intelligent plants. With the digital revolution, the development of new generations of mobile networks, the frontiers between the physical and digital worlds are disappearing to give life to an interconnected 4.0 factory in which people, machines and products interact. Industry 4.0 is a real challenge and an opportunity for the international industry.

Driven by the emergence of new technologies, Industry 4.0 refers to a new generation of connected, robotic and intelligent plants. With the digital revolution, the development of new generations of mobile networks, the frontiers between the physical and digital worlds are disappearing to give life to an interconnected 4.0 factory in which people, machines and products interact. Industry 4.0 is a real challenge and an opportunity for the international industry.

Industry 4.0: Origin, definition and Implementation

The term Industry 4.0 first appeared at the World Industry Forum in Hanover in 2011. The project "Industry 4.0" or "Industry of the Future" represents a new way of thinking about the means of production. The 4 is to mark this 4th industrial revolution.

A new industrial revolution is beginning

1-The 1st revolution : Mecanical production

It dates back to coal mining and the development of the steam engine by James Watt in 1769. This will radically transform the way of manufacturing. Indeed, craftsmanship will be replaced by mechanical production, factories will replace the factories and workshops … In the factories, the revolution corresponds to the use of the steam engine as an engine to power the machines allowing increased rates. This leads to a more important manufacture, and gives life to products in small series.

2- The 2nd revolution : Massive production

The second was brought about by the use of oil and electricity at the end of the 19th century. This will allow the modernization of the means of production. The automotive and chemical industries will take full advantage of it. From now on, production machines were no longer "steam-powered" but "electric". This period corresponds to the introduction of Taylorism and assembly line work making unskilled workers productive. We speak then of mass production of identical products.

3- The 3rd revolution : Automated production

Then, a third revolution took place in the middle of the 20th century with the advent of electronics, telecommunications and computers. These different disciplines will allow the implementation of important automations which will relieve the workers of the most difficult tasks. This is the beginning of robotics, the flexibility of production tools and mass production. Moreover, some situate this 3rd revolution a little later, at the beginning of the 21st century. It would be based on the energy transition (renewable energies, energy producing buildings and energy storage capacities) as well as digital technologies. Indeed, this would have marked the end of the exploitation of fossil fuels (coal, oil, …) and the advent of clean energy (sun, air, water). Finally, one of the important characteristics of this third revolution is the notion of mobility (of goods and people).

4- The 4th revolution : Connected factory

Today, it is no longer a question of a means of production producing (or rather reproducing) a product thousands of times over. We have entered the era of product customization. The consumer wants a completely personalized product, which does not look like the one of his neighbor. Industry 4.0 is committed to meeting this demand for unique and personalized products while maintaining equivalent costs, despite the low production volumes involved. This is why one of the challenges of this 4th industrial revolution is to succeed in connecting the customer's need to the production organ. This connection cannot be made without the contribution of new technologies, which will have to be exploited in this "new factory"…

Some protocols for Industry 4.0


MQTT (Message Queuing Telemetry Transport an ISO Standard "ISO/IEC 20922") is the communication protocol for machine-to-machine (M2M) connectivity. It is the technology that allows indicators or devices to communicate with each other wirelessly. As such, M2M is considered one of the fundamental elements of the Internet of Things (IoT), bringing many benefits to the industry through its wide range of monitoring and control applications.

This protocol brings a lot of security to companies, since these devices are connected to the servers, allowing the choice between storing the data recorded in the local servers or external servers, thus offering a secure service for the confidentiality of the recorded and saved data.


BACNET is the communication protocol used for energy efficiency and building automation. This protocol has been created for all systems, whether they are air-conditioning, lighting or security systems.

By implementing this protocol in buildings, costs such as engineering, training and maintenance costs are reduced throughout the life cycle of the building. This means greater transparency and efficient operation of the building for the company.

Communication structure for Industry 4.0

Industry 4.0 is characterized by very advanced automation and digitization processes. From the production and service management point of view,Industry 4.0 focused on the establishment of intelligent and communicative systems such as Machine-Machine and Human-Machine Interaction, processing a flow of data from the interaction of intelligent and distributed systems. The advantages of Industry 4.0 are: flexibility, agility, autonomy, automatic decision making, efficiency and cost reduction.

The implementation of Industry 4.0 should be interdisciplinary. Several authors have described the basic elements guiding Industry 4.0.

1-The Industrial Internet of Things (IIOT)

The Industrial Internet of Things is defined as the use of Internet of Things technologies in the industrial sector. The Industrial Internet of Things integrates Big Data, machine learning , as well as machine-to-machine.
The Industrial Internet of Things represents a form of the rapid evolution of digital transformation. It concerns all sectors, from energy production to agriculture and municipal management.

In order to understand what the Industrial Internet of Things (IIOT), it is important to understand what the Internet of Things (IOT)

Internet Of Things (IOT) refers to a growing number of objects connected to the Internet allowing communication between our physical objects and their digital existence. Between 2015 and 2025, 150 billion objects will be connected to each other, to the Internet and, in fact, to several billion people around the world. Therfore, the Industrial Internet of Things (IIOT) consists, thanks to these objects, in identifying and communicating between all the links of the industrial value chain: machines, products in the process of being manufactured, employees, suppliers, customers, infrastructures, etc.

The IoT market attracts many operators who invest in hardware, software, networks and connectivity and associated services.
Of course, there are the historical experts such as Advantech, Nexcom, Schneider Electric, ABB, Siemens, Bosch, Samsung and others. But, as IoT is not limited to the hardware aspect, other companies specialized in software are involved, such as: Microsoft , IBM, Google , Amazon , CISCO, …

The IIOT architecture is organized on 4 layers as shown in the following figure (1).

Figure 1 : Architecture of IIOT [1]

2-Cloud Computing

Industry 4.0 aims to make more dynamic the production and logistics processes that are currently planned, controlled and executed in a static way. The manufacturing industry must evolve in order to respond precisely to the needs of its customers and anticipate the arrival of competitors with disruptive approaches. The cloud computing represents one of the major elements of this new interconnected system linking machines, management methods and products.

3- Smart and Big Data

Big Data represents the massive amounts of data, structured or unstructured, that are collected by the various information tools. They have been used primarily in industrial software (PLCs, robots…) for many years. Today, we can add the connected objects (IoTs) that the factories of the future will be equipped with. This source of information is mainly used to control one aspect of the process at a specific time. The data is in exotic formats with little relevance. The large quantities stored then become quickly inoperable by conventional database and management tools.
This is where Smart Data analysis and representation methods come into play. Smart Data will contribute to more modeling, optimization and flexibility. By modeling production cycles using historical environmental data, we will be able to optimize the production tool in a global way. Real-time analysis will bring instant optimization and flexibility.

In usual computing, regardless of the level of complexity, it is a model created in advance that determines the actions of the program. In the case of a Smart Data approach, it is statistical rules that allow the program to build the model from the collected data.

The world of computer research is full of initiatives to generate these models quickly and with the least human intervention. Machine Learning is an Artificial Intelligence technology that allows computers to learn how to predict results. It takes data analysis to the next level.

There are different branches of Machine Learning:

  • Supervised Learning: The algorithm first needs to be presented with examples validated by the Data Scientist. The algorithm will first perform data associations that correspond to the examples. In a second step, the objective will be to predict the new data.
  • Unsupervised learning: The algorithm itself classifies the data into homogeneous groups in order to determine examples.
  • Reinforcement learning: Each branch is composed of various algorithms that will tackle families of problems.


Numerical simulation is one of the main technologies of the industry 4.0. Today's businesses, whatever their sector of activity, are facing increased competition. To achieve its objectives, the company must adopt or develop high value-added solutions. They have to face many challenges, such as the ability to innovate and improve product quality while optimizing production costs and time.

for process modeling in the context of Industry 4.0, simulation tools have a very important role because they allow :


By visualizing the behavior of the product in its final environment, it is possible to anticipate design obstacles. It also allows to engage more serenely in the development of new products.


The development of new products is often limited by physical prototypes or the outsourcing of calculation notes. These constraints in terms of costs, deadlines and outsourcing are a real brake on new products. This is why having an in-house digital twin for unlimited testing of different design alternatives very often makes the difference in this race for innovation.


In terms of optimization, the need can be divided into 2 major topics: product improvement and reduction of its development cycle.

It is now easy to compare different versions of simulated products and to conclude on the relevance of the modifications. The user can also use exploratory strategies to test a large number of variables. Typically, the approach consists of making the part lighter and saving material while ensuring the reliability of the part. Fatigue studies are more and more used to overcome life expectancy issues.

Technical teams also face a major challenge with development times. We know the importance of being a pioneering player in its market. Adopting validation solutions in the company allows to save a lot of time thanks to anticipation and autonomy. These gains are all the more important with simulation integrated into CAD because of the parallelisation of actions.

Figure 2 shows the domain areas of simulation

Figure 2 : the domain areas of simulation [2]

5- Augmented Reality (AR)

Virtual Reality and Augmented Reality play a role in the early steps of innovation (defined as Industry 4.0). At this stage, the optimization and improvement of productivity (quantity, quality, speed, flexibility) are more important than in the later stages of innovation and true business transformation.

The use of Augmented Reality can accelerate the whole production chain; up to the use of Augmented Reality in maintenance. Just think about how simulation prototypes are built, in combination with the appropriate data.

And then, of course, there is the possibility of putting a virtual overlay on the real world. It is based on the right data and information, in all kinds of industrial and production environments, using devices such as telephones, RA/RV glasses. These are probably the best known illustration of the combination of Virtual Reality / Augmented Reality and Artificial Intelligence tools.

The most well known applications of AR/VR include factory design, production, education, collaboration, assembly, safety, testing, and digital prototyping, to name a few.

The enhancement and immersion of customer-side experiences (the key to AR/VR) are also very important. As a result, marketers should also pay attention to this, especially in product manufacturing, where leveraging manufacturing technology expertise reinforces the perception of the technological value of the company and the product. So, no, it is no coincidence that many cases of AR/VR use in manufacturing attract a lot of attention, for example, in the automotive industry (and certainly luxury car manufacturers).

With the right equipment and solutions, plant and logistics personnel can also perform their tasks better. By having the information they need right in front of their eyes; in addition to their brains, this frees up two of their main work instruments: the left and the right hand.

Figure 3 shows the most relevant tasks related to industrial environments and manufacturing fields where the AR brings value.

Figure 3 : Value of industrial AR across I4.0 [3]

6- Cybersecurity

The first point of the factory of the future is cyber security. The first thing you have to see when you talk about cybersecurity is the physical risk. You have to physically protect the data so that no one can access it. Operators have created systems that physically protect millions of data stored on different servers.

The second risk is linked to digital intrusion. These operators have set up software that allows them to "sniff" all communications between all the plant's equipment. An alert is sent if the slightest problem is detected on the network. Finally, the last risk is related to external equipment imported into the plant. To protect itself, the installation of a system to decontaminate USB keys and hard disks is essential. Thanks to it, the risk of importing viruses into the factory is greatly reduced.


[1] S. Li, L.D. Xu, S. Zhao, The Internet of Things: A Survey, Inf. Syst. Front. 17 (2) (2015) 243–259,

[2] D. Mourtzis, M. Doukas, D. Bernidaki, Simulation in Manufacturing: Review and Challenges, Procedia CIRP 25 (2014) 213–229,

[3] D. Mourtzis, V. Zogopoulos, E. Vlachou, Augmented Reality Application to Support Remote Maintenance as a Service in the Robotics Industry, Procedia CIRP 63 (2017) 46–51,

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