AI & AUTOMATION
will make an impact . For example , using machine learning and computer vision to predict and identify faults in equipment before they occur , thus reducing production downtime and decreasing maintenance costs . Another challenge is establishing a culture of infusing AI into their processes through a test-and-learn culture .
For too long , organisations have talked about becoming ‘ data driven ’ and this has generally not worked as well as it had been hoped . Manufacturers need to take a different approach that starts with understanding where value can be driven from new insights and then focus on the data needed to drive the insights that can then drive business value . Organisations need to become ‘ insight driven and data enabled ’ and not simply ‘ data driven ’ - only then will they really leverage the power of AI and big data . current workforce . Fortunately , Industrial AI solutions can help and not require process engineers to be data scientists .
MP : The key challenge in adopting AI will come down to manufacturers ’ ability to establish alignment across the organisation on some of the high-value areas where AI
PL : It is all about how attitudes towards data have changed . It was previously seen as a necessary evil but is now the number one asset in a business . Typically this drives an obsession with big data labels but it is what you do with the data that matters – using the likes of AI / BI / IoT etc to turn that data into a truly valuable asset . The automotive industry is the prime example – using and selling the data produced by a car . Interestingly , we now almost take ‘ cloud ’ for granted – had we answered this question 24 months ago , cloud would have been the first consideration , but it is now table stakes . It is no longer if a business will go cloud but more a question of what type of cloud / cloud use ? – We have moved far beyond the infrastructure conversation – the how and into the what – and into the why a business looks to embrace digital . manufacturingglobal . com 63