By Johan Potgieter, cluster industrial software lead at Schneider Electric.
Following a recent annual meeting of the World Economic Forum (WEF), industrial artificial intelligence (AI) has joined the ranks of the world’s superheroes. The WEF announced that 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 is 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 finding 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 frees operators to focus on strategic problem solving rather than tactical manipulation.
Industrial AI offers the following important benefits and improvements:
• It can optimise production processes, reduce waste, and manage resources more effectively.
• Predictive maintenance can pinpoint equipment failures before they occur.
• Computer vision and other industrial AI technologies can improve quality control by detecting defects more accurately than humans.
• Supply chain optimisation (SCO) can predict demand, optimise inventory levels, and reduce logistics costs.
Johan Potgieter.
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 for teams within an organisation. It is 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 By using ML, KA curates content, filtering out poorly rated, unused and outdated data. 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 emails 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, while enhancing decision making and precision, which in turn extracts insight from both structured and unstructured data.
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