Quality during Design

AI in Design: Coming Full Circle


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As a Generation X engineer, I've watched design processes evolve from manual drafting kits and hand-derived equations to sophisticated CAD systems powered by artificial intelligence. What fascinates me most isn't the replacement of skills but their enhancement. The engineering fundamentals I learned decades ago haven't become obsolete. They've become more powerful when paired with AI and machine learning tools.

Today's design engineers have unprecedented autonomy. Tasks that once required specialized computing power and expertise are now accessible through AI-enhanced software. This democratization of advanced capabilities doesn't diminish the value of engineering judgment; it amplifies it. Understanding the underlying principles remains crucial for effectively leveraging these powerful tools.

If you're feeling overwhelmed by the pace of technological change in engineering design, start with foundational machine learning and AI prompts. Take a course that is an overview of how it works (I doubt you'll need to learn to code). From there, focus on applications most relevant to your work. Start with the software tools you already use for engineering. Is there an option to enhance it? Critically think about the assumptions and models it's using and always evaluate the result.

Text me about how you're incorporating AI into your design processes or what concerns you have about adopting these new tools. 

Visit the podcast blog for a graphic about AI hierarchy, ideas of how to use AI in different steps of product development, and my extra thoughts about this topic. 

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ABOUT DIANNA
Dianna Deeney is a quality advocate for product development with over 25 years of experience in manufacturing. She is president of Deeney Enterprises, LLC, which helps organizations and people improve engineering design.

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Quality during DesignBy Dianna Deeney


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