Why Should Manufacturers Adopt AI and Big Data?
Whilst the drive to digitally transform the manufacturing industry has been a topic of conversation for the last decade, recent events have only increased the need for the agility, scalability and resilience that Industry 4.0, smart manufacturing capabilities can provide. Speaking with Cobus Van Heerden, Senior Digital Product Manager at GE Digital, Mark Powell, Partner, EY (UKI Consulting), and Phil Lewis, Vice President, Solution Consulting EMEA at Infor Manufacturing Global looks at how technologies that harness AI and Big Data can help manufacturers unlock real-time operational visibility to achieve improved process reliability and performance.
What are the current applications of artificial intelligence (AI) and Big Data in the manufacturing industry?
CVH: Industrial AI uses a combination of targeted AI technologies, data, physics, and deep domain knowledge to solve key industrial business challenges. Traditional AI mimics human intelligence, whereas industrial AI builds upon it to unlock insights and determine causal knowledge in high-stakes, dynamic, and variable industrial environments. In Manufacturing, Industrial AI can be used to detect and predict key process and asset problems to help companies optimize their operations including capacity, quality, and cost structures.
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 the 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.