TECH & AI
“ Now that AI is taking hold in manufacturing , its value is evident in improved product quality , more efficient production and fewer resources required ,” Brandon says . “ The real excitement comes from connecting the entire manufacturing process , from raw materials to the final product .”
Brandon sees AI as a tool to connect manufacturing workflows from end to end , enabling real-time data access and analysis to optimise processes .
“ We ’ ve implemented point solutions , such as computer vision AI for visual inspection , to detect defects in production ,” he says . “ This can then be extended to root cause analysis by adding traditional manufacturing data . Once we identify root causes , we can create alerts or automation to prevent defects .”
This level of automation , Brandon suggests , will transform the industry in the near future .
“ These solutions don ’ t replace humans , they augment their roles by providing new upskilling and enabling data-driven decisions ,” he adds . “ This is already happening and the industry is starting to see the benefits .”
Despite the promise of AI , the adoption process has been slow due to a myriad of factors – including of course , the dreaded problem of data siloing .
“ Manufacturing generates vast amounts of data that ’ s crucial for process automation , but connecting and ‘ right-sizing ’ that data for AI use cases has always been challenging ,” Brandon explains .
Fabien adds : “ Factories rely on a mix of old and new systems that produce data in different formats , preventing a clear view of operations . This leads to inefficiencies and hampers productivity .”
To overcome these challenges , Fabian argues that integrating AI with existing systems , such as CRMs , ERPs , PLMs and MES , is critical . AI can enhance these systems by providing more flexibility and speed , enabling manufacturers to make better decisions and operate more effectively . Since 2019 , GFT and Google Cloud have partnered to do exactly this ,
70 March 2025