How do we make smart manufacturing part of our DNA in America? What’s preventing small and midsized companies from adopting smart technology? How do we build a workforce capable of undergoing a digital transformation?

These are the questions CESMII is working on, under the leadership of CEO John Dyck, who joins the podcast to talk about the democratization of smart manufacturing.

From the challenges in rapidly training and retaining new employees to the growing significance of data engineering, we discuss the changing manufacturing landscape in the U.S. Is the convergence of Information Technology (IT) and Operational Technology (OT) an absolute necessity for smart manufacturing? How is the technical debt accumulated over the last three decades influencing manufacturers today?

Join us as we delve into the intricacies of data acquisition, efforts to standardize data architectures, the IT/OT convergence, micro-credentialing, and other factors that will instill in our listeners a “smart manufacturing mindset.”

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3 Big Takeaways from this episode:

1. Data architectures have to evolve from disparate silos to standardized platforms that can all work together on the shop floor: For decades, manufacturing has innovated one use case at a time, plant by plant. Now, each digital solution is vendor-specific and poses a major challenge to companies trying to create a single, cohesive data strategy. John shares how hundreds of organizations are currently working on creating standards to enable data to flow seamlessly in manufacturing operations.
2. Standardization will democratize smart manufacturing in the U.S.: If manufacturing can devise an open-source, interoperable language and architecture for data which will enable any new software and hardware to work together, then small and midsize businesses have a chance at digital transformation. Not only will standardization democratize smart manufacturing on the enterprise level, it will also enable individual workers on the plant floor to be successful around data-driven systems without needing a degree in data science.
3. The U.S. needs to adopt a smart manufacturing mindset: In the same way as quality, safety and continuous improvement became an ingrained part of manufacturing culture decades ago, a smart manufacturing mindset has to become part of the DNA of every American manufacturer. This means having a data-driven mindset for business decisions, for thinking about the way workers do their tasks, etc.