Opinion piece: This looks like a job for industrial AI

Following a recent annual meeting by the World Economic Forum (WEF), industrial artificial intelligence (AI) has joined the ranks of the world’s superheroes.  The WEF stated, industrial AI has the ability to usher in an era of elevated efficiency, innovation, safety and sustainability, amplifying human knowledge to superhero foresight.

It’s quite a statement but also true.  Industrial AI it’s augmenting our abilities by simplifying problem solving.  Significantly, industrial AI is not displacing humans; it is equipping labour forces with self-learning and self-adapting technology that saves on time and improves productivity.

For example, in traditional manufacturing, countless hours are spent to find the right parameters to deliver products at scale.  With AI, parameters can be automatically refined in a virtual environment, before production.   AI-native control algorithms can handle routine manipulations in the equipment which free operators to focus on strategic problem-solving rather than tactical manipulation.

Industrial AI offers the following important benefits and improvements:

  • Efficiency – industrial AI can optimise production processes, reduce waste, and manage resources more effectively.
  • Predictive maintenance by pinpointing equipment failures before it occurs. 
  • Quality control – computer vision and other industrial AI technologies can improve quality control by detecting defects more accurately than humans.
  • Supply chain optimisation (SCO) by predicting demand, optimising inventory levels, and reducing logistics costs.

The Flash

A key part of industrial AI’s value proposition is Knowledge Automation (KA) which leverages AI’s language processing and machine learning (ML) to finetune relevant knowledge to teams within organisation. 

It’s designed to ensure that employees receive the information they need, precisely when they need it, thus eliminating inefficiencies caused by information overload or irrelevance.

How does this work? KA has the ability to evaluate vast amounts of content and variables at high-speed and far beyond human capability.  By using ML, KA curates’ content, filtering out poorly rated, unused and outdated content. 

KA can therefore assist organisations in automating and augmenting business processes with relevant knowledge, improving customer service, compliance and decision-making.  It makes companies more efficient by automating the flow of strategic information.

The cyberhero

The concept of Data Value over Volume – another important benefit of industrial automation – emphasises the importance of the quality and usefulness of data rather than just the quantity.

Data Value Over Volume leverages AI by focusing on extracting meaningful insights from data rather than accumulating large quantities. In the context of big data, it forms part of the five Vs: Volume, Velocity, Variety, Veracity, and Value.

Looking at real-life applications, industrial AI uses supervised learning to perform A-to-B mappings, such as classifying e-mails as spam or not, which is a fundamental way to create value from data. 

Furthermore, AI algorithms deliver data value by processing massive amounts of information, spotting trends that would be difficult for humans to discern whilst enhancing decision-making and precision which in turn extracts insight from both structured and unstructured data.

By Johan Potgieter, Cluster Industrial Software Lead at Schneider Electric

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