An increasingly data-driven future for manufacturing should go hand in hand with environmental impact.
On one hand, data sharing will enable manufacturers to decrease their carbon footprint, using lifecycle data collection and analysis to improve sustainability. But on the other hand, an increasingly data-driven future for manufacturing is not necessarily a very sustainable one. Training AI and its large machine learning models requires a lot of power. In fact, according to a paper of researchers at the University of Massachusetts, Amherst, the use of AI technology across all sectors produces carbon dioxide emissions at a level comparable to the aviation industry.
Being aware of this environmental impact is crucial, as data processing and AI is increasing and heading in the direction of ever-more complex models and wider adoption across industries. These developments should be considered when working towards environmentally responsible manufacturing as it poses disruptive potential for the future of data-enabled manufacturing