Technological advances have taken off exponentially in the last few decades. This has spawned an unbroken succession of revolutions that have completely overhauled our industries.
Only 40 years ago computer use was restricted to certain processes; nowadays computers underpin completely smart and independent industries based on technology and innovation.
In speaking of Industry 4.0 we are referring to those organizations whose activity depends on digitization using technologies such as the Internet of Things, Artificial Intelligence, Cloud or Big Data (to quote only the best known). These are industries with a great capacity of adaptation not only to the environment but also to ongoing changes, and a whole new world of countless possibilities is now opening up before them. Moreover, the importance of this fourth industrial revolution lies in the companies’ move towards a sustainable and increasingly ecofriendly model. This means that hyperconnectivity and the process automation capacity can prioritize such aspects as energy-saving and the use of secure, sustainable and competitive energy sources (both targets of the European Commission’s 2020 Energy Strategy).
Each second connected industries (buildings, robotics, energy networks, logistics vehicles, etc.) generate astonishing amounts of information, the vast majority of which is being wasted. A key theme to factor in here is that organizations are beginning to use IIoT technologies (Industrial Internet of Things) like Edge Computing and Digital Twins to extract deeper knowledge from their data with a host of concomitant advantages.
Data processing with Edge Computing
The billions of connected devices surrounding us glean a huge amount of information to be sent to the cloud, where great datacenters process it to draw certain conclusions or trigger certain actions. Problems crop up along the way; on most occasions nothing is done with the great amount of information we obtain. The best bet here would be to change how these (sometimes) inefficient devices work, making them much more autonomous and smart.
Edge Computing enables this device data to be processed closer to where it is created, instead of being passed on to datacenters and computation clouds. This offers us great advantages, allowing organizations to analyze their data practically in real time; this is considered to be a need in industrial processes like manufacture and production. In certain environments it is obligatory to reduce latencies; this means reducing network delays and consuming less bandwidth. This implies processing only specific data.
Analysts also stress Edge Computing’s potential. IDC, for example, forecast that by 2019 45% of IoT data will be stored and processed using this strategy.
In short, Edge Computing can be used as a Cloud-complementing technology to achieve such advantages as proximity (the devices are close to the equipment), locality (they work in isolation from the rest of the network), cybersecurity (data is reduced and decentralized) and lower energy consumption.
Simulating reality with Digital Twins
Digital Twins are virtual models of physical assets or industrial processes that continually learn and supply data to predict an industry’s performance. This is a game-changing technology focusing on improving equipment management and increasing productivity by streamlining processes.
These digital copies are used to make predictions about the behavior of the real world. A “digital twin” that acts like the physical object and is constantly being trained up by the data it is generating. As a result simulation can be used for pinpointing flaws, representing real-life scenarios and analyzing performance in a controlled environment. A manufacturer, for example, could try out adjustments in its working operations without interrupting production.
The Industrial Internet of Things marks the start of a digitized industrial era with the aim of driving completely efficient and effective management systems. Technological breakthroughs like Edge Computing and Digital Twins allow us to make the necessary changes to optimize energy use in industrial facilities, cut down consumption and use resources to hand more efficiently. From the innovation of products and services to predictive analytics, IIoT use cases will continue spreading inexorably through sectors with a great takeup potential, such as energy, transport, healthcare, agriculture or consumer goods.
Author: Eric Polvorosa Pascal, Marketing & Communications Specialist at GMV