Industrial Artificial Intelligence: Using data to take sustainability and efficiency to new heights

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For the past decade, big data has been one of the most talked about subjects in tech, and with good reason. Today, data isn't just a resource - it's one of the most prolific and valuable commodities available, along with the tools to capture, store, analyze, and protect it.

In fact, according to a new report from the IDC, stored data is projected grow by 61% to an incredible 175 zettabytes (just under one trillion gigabytes) by 2025.

Subsequently, there's also been a huge upsurge in the use of analytics software to fish actionable insights from this vast ocean of data. This, teamed with the more recent and rapid rise of industrial artificial intelligence (AI) technologies, with their ever-evolving capability to quickly process and analyze huge quantities of data, means that harnessing the power of the latest digital technologies presents endless opportunities to take industrial operations to new levels of optimization never seen before.

Data means nothing without the right analysis and action

Digital transformation, where technologies such as software-defined automation, cloud computing, industrial robotics, and AI are being implemented into everyday processes, has made one thing very clear - data is key in achieving the most agile, flexible, and efficient operation possible.

But to get the most value from our data, we must be able to quickly analyze, understand, and act on the insights it gives us.

And, when customized it for a specific facility, line, or product, this process can be even further optimized.

Industrial AI solutions and Schneider Electric

Finding the right data and developing models to provide the insights needed for effective production adjustments using older, more traditional methods can be difficult and time-consuming.

Today, solutions with AI inside can quickly and autonomously analyze a KPI's relationship to existing process variables and generate carefully calculated recommendations to be actioned by the workforce, or if preferred, adjustments can be made automatically and in real time!

For many years, our EcoStruxure open architecture has allowed our customers to securely collect and analyze critical IT (business) and OT (operational) data. With the addition of AVEVA, a global leader in industrial software, to the Schneider Electric group in 2023, we continue to evolve and excel, offering world class analysis and business intelligence software that empowers our customers to use their data to its fullest potential, helping them achieve optimal operation.

Together, we've been working on solutions for Industry with AI inside using the following technologies:

• Machine Learning: algorithms and code use data to automatically learn from underlying patterns without being explicitly programmed.
• Deep Learning: advanced machine learning uses neural networks to analyze and interpret data - particularly relevant for images and videos.
• Autonomous agents: Artificial agents such as collaborative robots or autonomous guided vehicles handle tasks on their own.
• Generative or GPT: use a type of AI model belonging to the realm of neural networks. Generative indicates the capability to create content, and Pre-trained means it has already learned or has access to a vast amount of information before being fine-tuned for specific tasks. Specifically, they use a Transformer model architecture to better understand information in context.

Whether it be to reduce material waste, increase energy efficiency and agility, lower engineering costs, or create a safer operation, AI can most certainly make a real and positive difference to the way we do business, and we are proud to be at the forefront of this next era in the industry.

AI helping to boost circularity and reduce e-waste

In my last blog, I shared the success story of Desoltik, a Schneider Electric partner that's pioneering the sustainable reuse of microchips recovered from used circuit boards, preventing them from becoming e-waste before their shelf life has expired.

By leveraging AI-based deep learning, visual recognition and an integrated robotics solution in their new all-in-one machine, they are revolutionizing the chip recycling industry. The Desoltik story is an excellent example of leveraging the latest technologies to shift toward increased sustainability in the electronics industry via circularity.

AI for low or no code development

Another great example of AI in our Industrial solutions is low or no code application development in EcoStruxure Automation Expert (EAE), our flagship software-centric industrial automation system.

Together with EAE, GPT technology uses object-based programming to leverage existing language-based operational documents that describe processes, to build control applicationsautomatically from the 300+ EAE IEC61499 libraries currently available.

This approach means there is no programming from scratch, reducing design and commissioning time and overall system implementation cost, as well as reducing time to market and increasing overall operational efficiency.

Leveraging the power of Industrial AI into the future

At Schneider Electric we are fully committed to providing our customers the best solutions, in a secure, responsible, and ethical manner. We combine our long-standing manufacturing and industry expertise to offer innovative AI solutions which empower smarter decision-making, greater agility, and increased environmental sustainability.

By integrating the latest and greatest in AI technology into our offers and solutions, we can not only deliver industrial AI-based optimization that leverages powerful analytical abilities to make the most of the valuable data generated in our customer's day-to-day operations, we can also take the overall efficiency and sustainability of Industry to greater heights.

Want to know more about harnessing the power of operational data with Industrial AI?

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