Aspects that are trending in Industry 4.0 in 2021

Artificial intelligence Artificial Intelligence and machine learning are driving innovations in all industries and functional areas. Specific AI hardware and new algorithms are being developed to optimize existing systems and propose new ones for manufacturing. Factories are beginning to integrate AI into their production systems and processes. Advanced AI makes it possible to perform predictive maintenance, cognitive computing, swarm intelligence, context-aware computing, intelligent machines, hardware accelerators, and generative design.

Advanced robotics

The most prominent robotic technologies impacting manufacturing include autonomous robots, collaborative robots (cobots), collaborative autonomous mobile robots, humanoids, mobile robots, cloud robotics, APIs, pick and place robots, and robot swarms. The use of robots offers greater precision and agility while enhancing the ability to rapidly develop customizable robots.

Additive manufacturing

Additive manufacturing, which began as a prototyping technique, is revolutionizing and decentralizing production. Advances in materials science and techniques allow easier fabrication of intricate structures and complex components. Additive manufacturing is making highly customizable and sustainable cloud-based production a reality.

Digital twin

Digital twin technology creates virtual models of industrial assets by combining dynamic real-time sensing and visualization data. Some of the promising use cases for digital twins include model-based design, virtual prototyping, virtual system validation, performance optimization, and evolutionary design. The use of digital cufflinks is driving Industry 4.0 manufacturing towards hyper-automation and they provide very important information on all steps of the manufacturing process.

Cybersecurity, transparency and privacy

The flow of information through connectivity in Industry 4.0 is raising concerns about security, transparency and privacy. Sensitive industrial data transmission and processing must be done securely to prevent cyber attacks on critical industrial facilities. Digital ethics and privacy, privacy enhancing technologies, self-adaptive security, end-to-end communications security, and the blockchain are some of the new developments on this front. The focus on cybersecurity must be balanced with transparency and privacy.

Cloud, Edge and Fog computing

The enormous amount of data generated by the Industrial Internet of Things (IIoT) is leading to the adoption of Cloud, Edge and Fog computing capabilities in Industry 4.0. Custom hardware and software solutions such as connected clouds, distributed clouds, distributed computing and storage, hybrid computing, mobile computing, and multiple access edge computing, among others, are fueling this Industry 4.0 trend.

Network connectivity

Network and connectivity are among the main driving forces to enable Industry 4.0. A number of technological developments, such as edge-to-cloud time-sensitive networks, gigabit ethernet, low-power and wide-area network (LPWAN), 5G, machine-to-machine communication (M2M), Time Sensitive Networking (TSN), the Ubiquitous radio access, the unified IoT framework and contactless networks drive factories to implement IoT to transform them into Industry 4.0 facilities. These technologies constantly improve machine-machine and human-machine communication, as well as data transmission. This improves speed, security, efficiency and reduces the cost of network connectivity.

Internet of Everything

The real-time machine-machine, man-machine and man-human connection in real time make up the Internet of Everything in manufacturing. It includes IoT, Internet of skills, Internet of services, Internet of systems, and Plant IoT. Internet of Everything combines real-time data, machine intelligence, and human skills, resulting in faster, more efficient, and more profitable manufacturing processes.

Big data and analytics

The scale of industrial data collection is finally enabling factories to transition to Industry 4.0 facilities. Big data is complex and valuable only when it is captured, stored, and analyzed quickly and cost-effectively. Advances in using data to gain valuable insight into manufacturing systems, coupled with the availability of real-time and immediate data, open up opportunities for prescriptive, predictive, and augmented analytics at different levels of a company’s manufacturing facilities.]]>