5 Top Trends for IIoT in 2020

1. The Continuing Importance of Edge Computing

Each device and sensor on a factory floor collects, processes, and packages up data for analysis. But with more IIoT devices in service, traditional cloud computing just can’t keep up. By working with data at the device level, you maximize performance, minimize costs, and improve overall latency and scale.

The speed of 5G networks will make edge computing even more valuable to industry, which will allow manufacturing to more quickly adapt to any type of connected solution and provide more intelligent, real-time analysis. With edge computing, automation and innovation will flourish thanks to an upsurge of APIs for higher programmability and the removal performance bottlenecks.

2. Digital Twins

According to Gartner, 75% of organizations taking advantage of IoT are using digital twins or are in the process of establishing the technology for them. Digital twins are the virtual representation of a physical device or object. The virtual twin allows research-and-development teams to gather data to simulate physical objects in real-time situations.

Manufacturing is at the forefront of this technology, as it allows these businesses to differentiate their products and services from competitors while establishing new revenue streams. As more factories adopt IIoT, as well as artificial intelligence (AI) and machine learning (ML), more manufacturers will use digital twins to simulate processes and streamline production.

3. Managed Cloud Services

The digital transformation and IoT-centric workplaces require a robust cloud service to support devices, applications, and databases to remain agile and competitive. IIoT also needs a robust cloud, which is leading to more reliance on managed cloud services in manufacturing.

Manufacturers are turning a distributed cloud that’s designed to execute at the point of need. The emphasis will be on a public cloud architecture that improves the management of information and relies on the services offered by public cloud providers. Hybrid options will still be there, but the shift will continue to move away from private clouds to a distributed public cloud architecture. These managed cloud services can be designated for specific device and data management, generating valuable and useful insights about connected products in manufacturing environments. 

AWS, Google Cloud, and Microsoft Azure are already on board with this trend, and IoT data platforms are quickly connecting, too.

4. The Role of AI

AI and ML have been trending upwards for the past few years, but we can expect to see a greater connection between AI and IIoT. AI will drive—and improve—IoT’s decision-making process. AI in IoT pushes computationally intensive analytics to the edge for scale and performance. That includes APIs for custom programming and load-balancing and distributed capabilities.

Manufacturers need the capability to granularly define analytics and machine-learning models on the platform for greater performance and faster response times. How can you attain this? By training data. This is the key to manipulating the output data used to set up ML models and enable automation and decisioning to benefit a plant in real time.

In addition, data and infrastructure management solutions will likely continue to expand their use of AI and ML technologies to deliver more automated IT operations to companies. These AI-driven systems will manage more day-to-day tasks, as well as strengthen policies and anticipate and respond to potential threats and challenges.

Altizon Systems How The Io T Is Enabling Energy Savings For The Smart Factory Of Today Fig

5. The Human Element

Industry 4.0 revolves around advances in technology. AI, edge computing, virtual testing, and IIoT are all important drivers of the new manufacturing plant. But none of this works without the human element. While automation will continue to shift plant personnel roles away from tedious, repetitive tasks, employees will move on to decision-making roles based on data support.

To have successful IoT deployments, human workers need to think differently on the job, and that will require an on-going effort to train employees for often high-tech tasks. Human interaction is necessary to update and monitor IIoT devices, requiring new skills. Employees will also need to reshape their activities on the factory floor, and management must have a better understanding of how data generated from the devices will impact the supply chain.

Machines aren’t replacing humans. Instead, there’s a new synergy between human and machines to ensure streamlined production and processes. This means investing time, budgets, and energy to ensure that it’s done right, and that involves recognizing where the new job opportunities will be and what type of retraining is necessary. 

We can expect to see these trends and predictions (and more) play out in 2020. I, for one, am looking forward to seeing IIoT continue to improve product development and delivery, making factories even more efficient, ensuring greater safety, and advancing the skillsets of manufacturing employees around the world.

Ranjit Nair is CTO and Co-Founder of Altizon Systems.

Source link