Capgemini Engineering
AI APPLICATIONS
Understanding AI to successfully improve manufacturing operations Undoubtedly , the uptake and implementation of AI have accelerated in recent years . According to Antelo , this acceleration has come from the original equipment manufacturers ( OEMs ) as there is a push to edge computing in the industry . He adds : “ This [ edge computing ] allows AI algorithms to run very close to the machines without a significant investment in Industrial Internet of Things ( IIoT ) or cloud infrastructure .”
The abundance that data manufacturers can obtain has also allowed for the increased adoption of this technology , which relies on data to create efficient algorithms . Spooners explains : “ Due to the advancements in machine learning , all of this data can now be utilised to create intelligence about what is and isn ’ t working in the end to end manufacturing process . Ease of accessibility and the rapid decrease of cost of the “ computational power ” needed to run the machine learning algorithms on this amount of data has helped increase the adoption of this technology .”
“ Data is the main ingredient that helps manufacturers utilise AI ’ s power – whether that be sensor data , vibration data , audio data or image data ,” added Spooner .
It is key , however , that when looking to implement AI technologies manufacturers understand how to effectively scale this technology , to do this there needs to be a level of expertise and knowledge around the best practices when implementing AI . Expanding on this , Antelo said : “ Many companies have tried unsuccessfully to incorporate AI in their manufacturing process and get stuck in “ pilot purgatory ” where they are unable to scale their projects . Some early AI adopters have managed to deploy machine learning algorithms , but many are stymied by scaling them .”
Capgemini Engineering
Capgemini Engineering has more than 52,000 engineer and scientist team members in over 30 countries across sectors including aeronautics , automotive , railways , communications , energy , life sciences , semiconductors , software & internet , space & defence , and consumer products .
98 December 2021