AI Transforms Manufacturing Processes

Next to many other different industries which are already working and implementing AI solutions, some of the most productive domains of deploying artificial intelligence today, no doubt, is the area of manufacturing. Machine learning algorithms are seen as the next frontier to improve products and flexibly fine-tune them to market demands. Developing new business models and distribution methods is another positive outcome of AI. Thus, artificial intelligence is causing a revolutionary shift of historical proportions. Sometimes it’s called “Industry 4.0“, referring to previous transformations of the industrial world.

No wonder then, that AI is seen as the great enabler of higher production yields, improved asset tracking and inventory management. All this is feasible through efficient real-time process visualization and predictive modeling based on the observation of large data sets. Management consultant McKinsey estimates that machine learning will reduce firms’ errors in supply-chain forecasting to the tune of 50 percent, thereby cutting lost sales by 65 percent. Accurate demand forecasts will lower energy costs, improve delivery performance and maintenance procedures. 

A point in case is the U.S. manufacturing conglomerate General Electric. In 2015, GE introduced its “Brilliant Manufacturing Suite“. It links design, engineering, manufacturing, supply chain and distribution in one worldwide intelligent system, powered by their own industrial Internet of Things, called “Predix“. By 2020, GE’s Predix platform is expected to process one million terabytes of data per day.

Similar efficiency and transparency strategies are pushed by other tradition-rich industrial giants, such as the German companies Siemens and KUKA. Siemens has launched its own IoT platform called “Mindsphere” to tackle the nitrous oxide emissions of its gas turbines: “Our AI system was able to reduce emissions by an additional ten to fifteen percent,” reports Dr. Norbert Gans of Siemens Corporate Research. Likewise, the world-leading Japanese robot vendor Fanuc is developing its FIELD platform by partnering with AI chip supplier Nvidia. KUKA, the well-known German robot pioneer, now owned by Chinese investors, makes great strides to get rid of the safety barriers between robots and human workers, allowing them to work side by side.

Collaborative robots, or “cobots“, are a rapidly expanding segment of artificial intelligence. Being no longer stationary but rather mobile, cobots are equipped with complex visual and motion sensorics, even speech recognition, to keep them from bumping into each other or hurting their human colleagues next to them. Workplace safety, therefore, is a major goal when deploying intelligent production systems.

The big fear, of course, is that in time cobots would replace human workers on a large scale. It has happened before, when back in the 1950s and 60s automation took hold in traditional factories, still based on human expertise and craftsmanship. It has since been offset by retraining workers for higher-level tasks and qualifications, and raising the level of education to avoid massive disruptions in the labor markets.

But the next wave of intelligent factory automation clearly is upon us. The future of industrial manufacturing looks to be one efficiently interconnected economical system that will produce and deliver fully customized consumer goods and services – at lower prices.


Varsha Shivam

Varsha Shivam

Varsha Shivam is Marketing Manager at Arago and currently responsible for event planning and social media activities. She joined the company in 2014 after graduating from the Johannes Gutenberg University of Mainz with a Master’s Degree in American Studies, English Linguistics and Business Administration. During her studies, she worked as a Marketing & Sales intern at IBM and Bosch Software Innovations in Singapore.

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