Discover how predictive analytics, machine learning, AI (artificial intelligence), and VR (virtual reality) reshape some of the ways we approach design. In this episode, we journey from the origins of predictive analytics to the convergence of big data, IoT, digital twins and more, paving the way for innovative product development. We’ll also discuss the potential of virtual reality to enhance collaboration and communication within design processes.

This episode isn’t just about embracing the latest tech trends; it’s about knowing when simpler solutions will suffice and the critical role of data stewardship. This overview will help you to understand the big picture of where these tools fit into your design process. Listen-in so you can better choose when to use them to optimize your design engineering endeavors, or not.

How do you know if any of these solutions are the right fit? One way to do it is to use a common quality tool: a scorecard. Dr. Robert Cooper explains how to do this for AI in his blog post: Selecting the Right AI Solutions for Use in New Product Development – Knowledge Hub 2.0

Other links:

Predictive Engineering Analytics: Overview & Benefits | Neural Concept

AI & VR in Product Development Pros & Cons – Cambridge DT

AI-Driven Decision Making: Your Next Step in Harnessing Data | Fullstory

Predictive modeling, analytics and machine learning | SAS UK

Dianna referenced an episode of Speaking of Reliability: SOR 1010 Uneasiness with AI – Accendo Reliability

Dianna also mentioned accelerated life testing: Results-Driven Decisions, Faster: Accelerated Stress Testing as a Reliability Life Test

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