Six technologies for Industry 4.0
The concept Industry 4.0 was given birth by the German government to describe a vision of hyperconnected manufacturing processes, a new model based on data. It seeks deep changes and evolutions, to such an essential level, that it has already been given the name of fourth industrial revolution. Governments and supra-national institutions recently adopted this belief by approving initiatives and regulations to foster the adoption of this new paradigm by private companies.
According to Gartner, the path of innovation to industry 4.0 is highlighted by a digital convergence between industrial and business components; and between manufacturing models and internal processes as well. Gartner highlights, among other things, the combination of data from external and internal sources to improve decision-making; the development of digital skills for a better integration and management of resources within the organization, including security, cybersecurity and risk control; the understanding of how technology can affect the Industry 4.0 localized manufacturing; and finally, the simultaneous work on the development of smart products and manufacturing processes.
As we have already stated, the new model of data-centric industry requires a deep transformation based on the intelligent integration of ICT in the heart of companies. Below, we highlight six of the technologies on top of wich the future industrial model will evolve:
Six essential technologies for the transition to Industry 4.0
1- IIoT and cyberphysical systems – The concept of IIoT (Industrial Internet of Things) refers to the use of IoT technology in manufacturing processes. The cyberphysical systems are devices that integrate processing capabilities, as well as storage and communication capabilities, in order to control one or more physical processes. The cyberphysical systems are interconnected between them and to the global network through the IoT paradigm.
2- Additive manufacturing, 3D printing – Allows, among other things, the hypercustomization of the product -which is inherent to the Industry 4.0 paradigm and to the concept of servitilization-, cheaper processes of products manufacturing regardless of the number of produced items, and.also makes much easier to produce small series of prototypes.
3- Big Data, Data Mining and Data Analytics – The amount of information currently stored in relation to different processes and systems (both industrial and logistics), services (sales, connections between users, power consumption, etc.) or data traffic(logs in routers and equipment, etc.) is huge, thus impossible to manage manually. A comprehensive analysis of these data can provide valuable information about those processes; and also can prevent problems in particular industrial processes through the detection of abnormal measures (without the need to have previously defined to what extent the measuring results are or not abnormal); or even determine which events are related in more complex processes, thus facilitating management through prediction, knowing that an event may trigger another with a certain probability. Simulations can also predict what resources that will be needed, and can optimize the use of those resources automatically, or proactively anticipate future events and needs.
4- Artificial Intelligence – In this landscape of a data centric industry, there an urgent need to extract value from large amounts of information, hence tools and technologies that are capable of processing in real time large those volumes of information are needed, being able to learn independently from the information they receive, regardless of the sources, and the reactions of users and operators (Machine Learning or Deep Learning technologies)
5- Collaborative robotics (Cobot) – This term defines a new generation of robots cooperating with humans closely, without the usually required security restrictions applied in industrial robotics typical applications. Is characterized, among other things, for its flexibility, accessibility, and relative ease of programming.
6- Virtual Reality and Augmented Reality Thanks to the increased accessibility and ease of use of these technologies in the recent years, VR and AR had become useful tools for optimizing designs, automation of processes, control of manufacturing and construction, workers training, and for maintenance and monitoring activities within industrial environments.
