The potential of AI and ML to unleash creativity and improve efficiency across a range of processes is one of its primary contributions to engineering. ES Chakravarthy highlights the ways in which AI algorithms can optimize design iterations, resulting in solutions that are more effective and economical. The automation of tedious work and the analysis of massive volumes of data free up engineers to work on more creative and advanced problem-solving. Engineers can save downtime and maintenance costs by anticipating future failures with machine learning models that collect real-time data from equipment sensors. By improving the longevity and dependability of engineering assets, this proactive approach to maintena...
The potential of AI and ML to unleash creativity and improve efficiency across a range of processes is one of its primary contributions to engineering. ES Chakravarthy highlights the ways in which AI algorithms can optimize design iterations, resulting in solutions that are more effective and economical. The automation of tedious work and the analysis of massive volumes of data free up engineers to work on more creative and advanced problem-solving. Engineers can save downtime and maintenance costs by anticipating future failures with machine learning models that collect real-time data from equipment sensors. By improving the longevity and dependability of engineering assets, this proactive approach to maintenance raises overall operational efficiency.
