AI for Every Manufacturer: Predict Failures & Boost Productivity with the Data You Already Have

Nitin Ranjan, Founder and CEO of Golgix

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Unlock the power of AI in manufacturing with practical insights that could save your plant thousands—without the need for a data science team.

This week, we sat down with Nitin Ranjan, Founder and CEO of Golgix, to explore the game-changing role of artificial intelligence in manufacturing. Nitin reveals how Golgix is breaking down the barriers to AI adoption, especially for small to midsize manufacturers, by turning existing plant data into actionable insights. Discover how AI can boost productivity, reduce downtime, and cut costs without the need for expensive, complex overhauls.

Through engaging stories and real-world examples, Nitin shares how manufacturers have saved millions in capital expenditures and created more efficient, less stressful work environments. This conversation goes beyond technology, focusing on how AI empowers people to focus on creative problem-solving rather than mundane tasks.

Inside this episode:

  • How to use the data you already have, with PLCs you've already deployed, to implement an easy AI solution.
  • Hear how one manufacturer cut downtime by 59% and saved $450,000 annually with AI.
  • Understand common AI misconceptions in manufacturing—like the myth of unusable data—and how to move past them.
  • See how AI software can be set up in two hours, delivering ROI in just 3 months
  • Strategies for building trust in AI systems among plant managers and operators to drive successful adoption.

Quotable Moments:

On the resistance to AI: "I think it's the perception problem more than the data problem. [Manufacturers] believe they don't have the data which can help solve the problem. The reality is they have the data; it's just buried under tons of other datasets."

"AI as a technology is open source and it doesn't really have an intrinsic value until it's applied. So you have to see where you are getting the most amount of data, right? And in manufacturing, all the way from procuring raw material to the way they ship out final goods, you have data coming through."

"If we don’t deliver value at speed, we are not an AI company, right?"

"We are not building technology just for business value; we are building technology for people. For the last 20-30 years, we have seen smarter machines and better processes, but what we have not seen is investment in people. The planned floor is full of chaos and uncertainty... nobody should live like that. Building this technology gives people that foresight and control, reducing stress and making their work more manageable."

3 Big Takeaways from this Episode:

  1. Manufacturers are sitting on a goldmine of data that, when properly leveraged, can significantly boost productivity and reduce costs.
    Most manufacturers have a wealth of data flowing from programmable logic controllers (PLCs) and other systems, but it often goes untapped due to lack of awareness or clarity on its value. By extracting and analyzing this data, Golgix has helped companies cut downtime by 59% and save $450,000 annually.
  2. The biggest barrier to AI adoption in manufacturing is not a lack of data but a lack of trust in that data.
    Manufacturers often believe they don’t have the right data to drive AI applications, but Nitin argues it's a perception problem rather than a data problem. By cleaning and interpreting existing data, Golgix helps companies build the confidence to use AI to make data-driven decisions.
  3. Adopting AI in manufacturing doesn’t have to be complex, time-consuming, or require extensive resources.
    Golgix’s AI software can be deployed in as little as two hours and shows a return on investment within three to five months, making it accessible to manufacturers of all sizes. The technology is designed to be user-friendly, with minimal training needed, so plant managers and operators can quickly see the benefits without being overwhelmed.

Resources in this Episode:

Connect with Golgix:

LinkedIn  |  Connect with Nitin on LinkedIn

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