AI – changing industry as we know it

Industry 4.0 and associated technology, such as the Internet of Things (IoT), Artifical Intelligence (AI) and robotics, have become part of the manufacturing vernacular, without many understanding their potential. Digital transformation offers great unmatched potential for manufacturers. Not only does it greatly improve communication between devices, systems and personnel both inside and outside of the company, but it also provides the directness to cut energy consumption, increases efficiency, and increasingly delivers even short-term ROI.

AI is one technology that will revolutionise the field. A recent report by Accenture showed corporate profits are said to increase by an average of 38% by 2035, thanks to the advanced deployment of AI into financial, IT, and manufacturing applications.
 
Transforming Industry 4.0

AI is becoming an important part of Industry 4.0. It brings with it the great potential for innovation to dramatically increase the productivity of industrial assets, better manage the evolution of the workforce, and greater energy efficiency.

Let’s take discrete and process manufacturing as an example. Here, asset maintenance is one of the industrial processes that is emerging as an early AI application. As a result, we’re seeing more manufacturers understand that predictive maintenance can be blended with the more traditional approach of preventative maintenance. The two, work hand-in-hand.

A great example of how AI is revolutionising Industry 4.0 and improving efficiencies on the factory floor is Variable Speed Drives (VSDs). VSDs are connected to motors on the factory floor. They attain data and insights into abnormal behaviours that could threaten a breakdown and thus flag these issues so that they can be repaired, or where necessary, replaced ahead of any catastrophic failure. The benefit here is that a piece of equipment on the factory floor is only replaced when absolutely necessary, saving the manufacturer all the costs associated with unnecessary interval maintenance and unplanned operational downtime. Machine learning also comes into play here as the analytical engines in AI quickly understand the normal operation of equipment in certain conditions and can reliably determine the health. AI can be running remotely in the cloud or it can be executed ‘at the edge’, ie on premise close to the equipment when necessary, to help in the early identification of many potential faults including, power generation turbine blade damage or plant motor coupling approaching failure.

As the benefits of humans and robotics working together are becoming more obvious, the Industry needs to prepare for change. How can we turn down the possibility of not having to work 24-hours a day and the ability to produce more consistent outputs? Industry 4.0 for many of us is just starting. If you only take one message from this, it should be that investing in technology including automation and robotics and incorporating AI, machine learning and IoT is central to improving productivity and increasing efficiencies and ultimately survival.

Martin Walder, Vice President of Industrial Automation at Schneider Electric