As the editor-in-chief of both Foundry Management & Technology and American Machinist, Robert Brooks brings over two decades of expertise to the table, specializing in primary metal production and foundational manufacturing processes. Delving into metal casting and manufacturing technology, Brooks and his editorial team cover topics from the molten metal pouring in foundries to the precision cuts made in machine shops, offering a comprehensive view of the sector's landscape.
In this episode of Great Question: A Manufacturing Podcast, Brooks tackles the emerging role of artificial intelligence in industrial data gathering. As the manufacturing world navigates the transition from traditional big data practices to AI-driven solutions, Brooks offers insights into the challenges and opportunities this shift presents. Drawing on his extensive industry knowledge, he explores how AI is being perceived and implemented across various manufacturing sectors, and what this means for the future of data management in industrial settings.
Below is an excerpt from the podcast:
In this installment, I'm going to raise an issue that I think is lingering in the minds of various manufacturers that I speak with concerning what they have long referred to as big data, meaning the huge volumes of information that accrue in manufacturing activities from older generation to production data to performance metrics. For the past two years, the discussion of big data has been subsumed by the growing awareness of artificial intelligence and the ability of large language models to detect patterns and simulate results and generate conclusions about present and future activities. At the International Manufacturing Technology Show, that is IMTS 2024, which I attended earlier this month, the novelty of AI capabilities in the manufacturing space was quite evident by the presence of tech giants like Google and Microsoft and Amazon. But exactly what this new visibility portends is still a question to many of the manufacturing figures that I have asked.
