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We are thrilled to announce IoT Now will be joining us as a Community Partner at World Summit AI Americas (May 4-5, Palais des congrès).
Here IoT Now share with us the 10 Best IoT Industry 4.0 Implementations.
Businesses in the industry 4.0 sector face unceasing demands to become faster, smarter, leaner, and more profitable. We’ve all heard of Smart Cities and Smart homes, but the fully automated and IoT-enabled Smart factory is also on the horizon. Indeed, it’s already possible today, says Darren Wall, freelance technology writer.
The IoT (Internet of Things) has proved its potential to revolutionise businesses across all sectors. When implemented correctly, it can streamline processes, improve decision-making and create extra value for stakeholders, partners and customers alike. It’s no wonder that it’s the main driving force behind Industry 4.0 – what has been described as the “4th industrial” revolution.
What is Industry 4.0?
Industry 4.0 refers to the process of digital transformation in manufacturing/production and related industries to create more value. Many consider the current digital transformation trend to be analogous to the 4th industrial revolution, hence the name.
Industry 4.0 is concerned with how manufacturing can transform, by using 3rd-party platform technologies, innovation accelerators, and IT/OT (operational technology). This means incorporating cutting-edge technologies across cybersecurity, big data, AR/VR, cloud computing, automation, AI and IoT, to digitally transform conventional processes and capabilities. The goal is to make businesses smarter and faster as well as more resilient and agile.
Here are some of the top Industry 4.0 use cases of IoT technology:
- Big Data and Analytics
As it stands, manufacturing businesses already produce copious amounts of data. This could come from IoT sensors, production volumes, sales forecast, and performance data, etc. They also have to deal with a range of external data points and factors, such as market conditions, politics, the climate and so on.
As it stands, manufacturing businesses already produce copious amounts of data. This could come from IoT sensors, production volumes, sales forecast, and performance data, etc. They also have to deal with a range of external data points and factors, such as market conditions, politics, the climate and so on.
However, problems usually arises when it comes to effectively storing, processing and utilising that data.
Manually collecting, organising, and sifting through data, not to mention gathering insights, is, historically, a time-consuming and laborious process. Worse, it’s a waste of human potential considering how efficient and adept technology is at handling big data. Big Data & Analytics tools are transforming this side of a business’ operations in to one that happens virtually in real-time and with vastly increased intelligence applied.
- Autonomous Robotics
While we might still be some way off humanoid robots, with human-like intelligence and dexterity, manufacturing automation is surprisingly mature. Robotics is already extensively deployed to perform repetitive, high-precision tasks in all kinds of production lines. The possible benefits of automated robotics in manufacturing are far-reaching:
- Facilitate continuous production with limited-to-no downtime
- Lower the risk of work-associated injuries from hazardous tasks
- Improved efficiency and productivity via fast and autonomous decision-making
More advanced robotics today don’t even require a human operator. They can self-navigate as well as itemise and step through a rapidly increasing number and variety of tasks.
- Simulations and Digital Twins
A digital twin is a virtual simulation or model of a real-world object, such as a piece of manufacturing equipment or an entire facility. The most common use case of these systems is to run simulations designed to identify inefficiencies and opportunities for improvement.
They can also be used to run pre-emptive tests of how a system or machine would perform in specific circumstances. What’s more, employees can be trained and educated using the equipment before being put in a real-life scenario. This can be particularly effective when combined with AI and machine learning technologies.
The author is Darren Wall, freelance technology writer. This article first appeared on www.IoT-Now.com
The World Summit AI team
Here is your global calendar for 2022 where you can meet your fellow World Summit AI community members:
World Summit AI Americas | 04-05 May 2022 | Montreal, Canada
americas.worldsummit.ai
World Summit AI | 12-13 October 2022 | Amsterdam, Netherlands
worldsummit.ai
