Technology Magazine April 2018 | Page 44

What does Wilkins believe is the greatest barrier impacting the marriage of manufacturing processes and deep learning ?
Finally , Wilkins explains how he believes deep learning will be harnessed by his industry in the future :

ARTIFICIAL INTELLIGENCE

predictive maintenance becomes more effective , because machines take note of all experiences that coincide with system faults and apply this information in future situations . It is even possible for a machine to analyse the data for each individual situation and decide the next action for itself . In some cases , the system may perform its own corrective function , otherwise it would alert an engineer . If the situation is particularly dangerous , it may shut down the system .”

What does Wilkins believe is the greatest barrier impacting the marriage of manufacturing processes and deep learning ?

“ One of the biggest challenges in the adoption of machine learning is data handling . Machine learning algorithms collect and analyse data , but irrelevant information can interfere with this process . Ensuring machine learning algorithms function in a way that benefits the business , manufacturers must understand their data and the exact functions they want machine learning to fulfil .”

Finally , Wilkins explains how he believes deep learning will be harnessed by his industry in the future :

“ Artificial intelligence is already being used to solve simple problems , such as AGVs overcoming obstacles , on the factory floor and along the supply chain . As the technology develops , we will see it being used to solve more and more complex problems .
“ Soon , this could lead to the development of collaborative robots that work alongside humans . They would participate in business meetings and adapt to changing circumstances . These robots would benefit businesses by being able to interpret and analyse larger amounts of data than the human brain to make informed decisions about predicted outcomes from so called soft interactions .”
44 April 2018