AI & AUTOMATION
70 % of manufacturers will use digital copies of the physical world ( digital twins ) to conduct simulations and scenarios by 2022
70 % of manufacturers moving into robotics will need operations talent to manage more automated and flexible production
“Digitisation is forcing manufacturers to reimagine their supply chains ”
MARK POWELL PARTNER , EY ( UKI CONSULTING )
PL : Textbook definitions of AI or Big Data miss the point that industries differ and will have drastically different demands for the technology . It is about the application of a given technology to a specific issue that a business may be experiencing . This issue may be an ‘ industry-standard ’ one , or something that arises in the configuration of the technology . But there is most value in the application of tools such as Big Data and AI to the critical 10 % of a business that is truly idiosyncratic . We classify this as a 60 / 30 / 10 split and it is how we look to apply these technologies to drive maximum value .
73 % of manufacturers plan to invest more in smart factories to support innovation and automation
70 % of manufacturers feel that robotics will drive the need for highly skilled workers registrar
Q . For manufacturers looking to adopt Industry 4.0 , smart manufacturing capabilities , why should manufacturers use AI and Big Data to do so ?
CVH : Smart manufacturing deploys industrial advanced analytics to predict future asset and process performance using real-time and historical data and optimising in a closed loop . This involves the use of AI and machine learning to enable process engineers to combine data across industrial data sources and rapidly identify problems , discover root causes of issues in the plant , predict future performance of assets , and automate actions employees can take to improve quality , productivity , and operations .
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