When a company wants to start in Industry 4.0, its managers will come across a number of concepts that have some technical complexity and that, in many cases, are not well explained or not in one place. In order to facilitate understanding and save searches regarding the vocabulary that is handled in the sector, we publish ed this basic dictionary of Industry 4.0 in which we briefly explain the most common concepts.
Industry 4.0: This concept requires an explanation in itself. When we refer to Industry 4.0 we are not only talking about incorporating a number of technologies into the different industrial or business processes, but it is a global concept that goes beyond the sum of its parts. The fundamental objective of Industry 4.0 is to improve the profitability and competitiveness of companies by incorporating a “digital layer” that encompasses all aspects of production and management, providing digital technologies in all links of the value chain. We talk about digital marketing, communication with customers by digital means and chatbots, the application of Artificial Intelligence in the different aspects of management and production, 3D simulation and digital twin, predictive algorithms, machine learning, Internet of Things, Big Data and many other tools that interact cooperatively, both with each other and with humans, simplifying decision-making and giving the company greater capacity to respond and to take advantage of resources.
Internet of Things (also IoT or Internet of Things): Using broadband connectivity (fiber optic, 4G, 5G) to communicate directly with each other, without having to go through human operators. This ranges from autonomous vehicles to communication between robots, cobots, sensors, data servers or industrial applications. The distributed architecture of the Internet ensures smooth communication between machines without the need for large central servers, so that each machine or object in general communicates with the person who needs it and when it needs it, either to receive or to transmit data.
Artificial Intelligence (AI): Computing systems based on algorithms and decision trees that are able to mimic (not replace) certain reasoning capabilities of humans in certain situations. For example, AI is used in the cameras of many mobile phones to determine for themselves the best level of light, brightness, color intensity and focus for a photo based on the elements that appear in it and environmental conditions. Artificial Intelligence is a technology designed for cooperation with humans in decisions that machines can make more quickly and efficiently. In addition, AI systems can “learn” to some extent of the experience, allowing them to improve their performance over time.
Chatbot: This is an application of Artificial Intelligence and Industry 4.0 to customer relationships. It allows them to establish a conversation with a machine, either by voice or through written chat, using a natural language that it is able to recognize and give an answer. It reduces waiting times, helps the user guide him when he has a problem at any time of the day and allows us to have a 24 hours /7 day service at an affordable cost. Virtual assistants of great technology companies, such as Siri, Alexa or Google Assistant, are examples of applying Artificial Intelligence to chatbots.
Cobots: Abbreviation of “Cooperative Robot”. These are industrial robots designed to interact with humans and function as their assistants, unlike large traditional industrial robots that must operate in isolated environments. In addition, cobots can cooperate and communicate with each other in a similar way as a swarm of bees or (algque already applied on many logistics platforms), so that they do not interfere with each other or with the humans around them.
Digital Twin: A digital twin is a virtual copy of a real environment. It can be applied to production lines, factories, complete companies, buildings, cities, etc. The digital twin presents, by virtual reality or augmented reality, the data provided by a multitude of sources of information (machines, sensors, computers, humans, etc.) and allows to interact with them, both in real time (visualization of data “touching” an element with a gesture, if it is a 3D virtual reality environment) and simulating different scenarios (what happens if I change site elements, if I increase the rate of production, what machine should replace, where the necks will be …) Its applications are almost endless.
Machine learning: Ability of machines or information systems to “learn” from experience. This learning can be directed by humans subjecting the system to training, can be automatic or can be based on “trial and error”. Machine learning systems typically use, to a greater or lesser extent, the three forms of learning. The self-driving car is the best example of this: First you have to train him to know what road markings are and road signs, then he has had to learn only in real situations (controlled by a human operator) and ask when presented something he does not understand, and then he has been allowed to travel in automatic mode to accumulate experience that is very complicated to program previously (interaction with pedestrians, unforeseen behaviors of other vehicles, etc).
Big Data: Big Data is the name that is led to the exploitation and crossing of large amounts of data from different sources to obtain results that were not evident with the naked eye, or directly new results. Most companies have a wealth of information that they don’t exploit properly. In addition to its commercial aspect and relationship with customers (something that large technology and corporations already do to offer us offers customized to our needs or interests) Big Data allows such interesting things as optimizing stocks, adapting production rhythms, predicting market behavior or improving preventive maintenance, among many other applications.
Virtual Reality and Augmented Reality: These are two types of communication interface with digital systems by humans. While Virtual Reality does not provide a completely digital environment in which we can “enter”, for example using 3D glasses and gesture recognition, Augmented Reality uses electronic devices to overlay a digital layer on the real world, so that we can access “overprinted” data about what we’re seeing. Neither technology is new, but it has been necessary to develop ultra-fast communication networks and increase the exponential computing power so that both can realize their full potential.
Additive Manufacturing and 3D Printing: These are manufacturing processes that do not require molds or physical patterns to manufacture components. 3D printing, which already allows to manufacture parts of the size you want and almost from any powdered or moldable material, is the maximum exponent of this manufacturing system that is already used in the aerospace, automotive, architecture or manufacturing of industrial and electronic components. The “mold” is a virtual 3D design that a machine or set of machines are able to manufacture on their own from raw materials such as plastic and composite materials, concrete or even certain metals.
Probably not all the terms related to Industry 4.0 (we would need an encyclopedia) are in this dictionary ( we would need an encyclopedia), but the ones that are handled more commonly. In future installments of our blog we will expand it with new terms.