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Top technology trends that drive manufacturing 4.0

Learn more about the 5 key digital technology trends that will shape the evolution of manufacturing as we know it today towards Industry 4.0.

Top trends Manufacturing

“The industry continues to evolve. Indeed, a number of trends are combining to transform manufacturing and, together, these trends can be referred to as “Industry 4.0”, says best-selling author Bernard Marr, and lists a number of top technology trends in his must-read article on manufacturing, that inspired us to write this piece.

When thinking of Industry 4.0, it's mostly disruptive digital technologies that come to mind, such as the internet of things (IoT), artificial intelligence (AI), edge and cloud computing, computer vision, automation, and others. Many of these have been around for a while, but they are now unleashing their full power in combination with each other.

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Trend 1: The industrial internet of things (IIoT) & cybersecurity 4.0

As IoT has been around for a few years and continues to spread into personal and business life, it has naturally made its way into manufacturing. Machines and vehicles are connected and share data via the IoT - the mid-term vision is that all devices in manufacturing communicate with each other seamlessly as humans do, but faster and more reliably.

However, as the number of connected devices in the IIoT grows, so does the surface for cyberattacks. Therefore, it seems important to us to mention cybersecurity 4.0 as a major technology trend. IT and security professionals in manufacturing will have to deal with increasingly complex threat scenarios that are also changing at an ever more dynamic pace.

Example for a basic security reference architecture in an IIoT environment

Trend Micro

Source: Trend Micro

Worth reading: Industry 4.0 - Managing cybersecurity in connected manufacturing & supply chains.

Trend 2: Edge computing

The fifth generation of mobile data network technology (5G) allows data to be transferred between systems in the IIoT on a larger scale and at higher speeds than ever before. This is a major driver for seamless communication between devices in manufacturing. On the other hand, more data is processed right in the devices - this is called edge computing.

IBM describes edge computing as “a distributed computing framework that brings enterprise applications closer to data sources such as IoT devices or local edge servers”. A surveillance camera that previously only sent raw video data to a video management server, equipped with powerful processors and AI video analytics, is now able to process data itself.

Thanks to edge computing in manufacturing facilities, instead of bold raw data, only lean results of data analysis are exchanged via the IIoT. This saves resources and also can help reduce the attack surface of networked systems.

Trend 3: Digital twins

A digital twin is a digital representation of a physical object. It includes the model of the physical object, data from the object, a unique one-to-one correspondence to the object and the ability to monitor the object. - Gartner

It's very likely that every physical object that can be described to the finest detail, will be digitally represented in the IoT. In manufacturing, for example, digital twins technology allows engineers to first test and simulate before investing time and money in developing actual products. Prototypes can be developed at the lowest possible risk.

Examples of robots in manufacturing represented by digital twins

Autodesk

Source: Autodesk

Digital twin technology helps fix bugs and evaluate functionality before even one part of a machine, system, or building is created. In other words: Digital twins help humans to make better and more educated decisions. This also applies to other areas, such as maintenance, which can be executed more efficiently (e.g. remotely) by using digital twins.

Worth reading: Why digital twins could be the next big thing in IoT

Trend 4: Computer vision & smart video surveillance

The smarter each individual entity in the IIoT gets, the greater the overall business value that connected systems will generate. In manufacturing, it is primarily sensors and the ability to process collected data via edge computing that make machines and other components smart. Computer vision in combination with AI makes blind devices “see”.

Smart video technology can help increase efficiency, safety, and quality in manufacturing. You don't necessarily need expensive high-end equipment to do this; even regular CCTV cameras, equipped with AI video analytics, can take on more complex tasks in an industrial environment than they are given credit for. Smart video cameras become all-rounders.

Example applications for smart video cameras in manufacturing

  • Supervise product finish and quality
  • Detect accidents with people involved
  • Accelerate and automate access control
  • Detect smoke and fire early
  • Keep aisles clear of obstacles
  • Comply with safety and health standards

Learn more about how to use Azena-powered video cameras in our manufacturing whitepaper.

Whitepaper CTA Manufacturing

Trends 5: Web3, Blockchain, NFT, Metaverse

Web3, also known as web 3.0, is a heavily discussed approach for a new iteration of the World Wide Web-based on the blockchain, including concepts such as decentralization and token-based economy. Metaverse also goes in this direction, but rather focuses on virtualizing private and business life as far as possible.

Distributed computing technologies such as blockchains and non-fungible tokens (NFTs) promise to create new opportunities for manufacturers to better monitor their supply chains and automate transactions along their supply chains. For example, many products manufactured in the future could be sold with digital NFT certificates.

Demo showcase of BMW Group's factory of the future

 

Source: NVIDIA

Visions like these will be a reality very soon, changing manufacturing from the ground up.

Conclusion: Much is possible, start early but small

With Web3 and the Metaverse, the wildest technology dreams seem to be coming true, though much is still in its infancy. IIoT, edge computing, digital twins, and computer vision in manufacturing can already be used productively today. Manufacturing 4.0 should focus on making the best use of modular architectures and data analytics to make business more efficient and secure.

First, take the steps that create maximum value for your business with minimal effort. Then expand gradually. At Azena, we support you in this approach, when it comes to getting more out of the surveillance cameras in your facilities.

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