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January 7, 2025 44 mins

In this episode, hosts Jen Ferrello and Jonathan Scott discuss, with guest, Oleg Shilovitsky, an industry blogger and expert in Product Lifecycle Management (PLM), the transformative trends in digital products and manufacturing for 2025. They explore the impact of graph technology and artificial intelligence on product lifecycle management (PLM), emphasizing improved collaboration, real-time integration, and innovative engineering workflows. The conversation also addresses challenges related to generational tech shifts, modernizing workflows, and the necessary evolution of engineering practices.

Key Discussion Points

Impact of Graph Technology:


  • The significance of managing relationships within product data.
  • Comparison of graph databases with traditional relational databases, highlighting their expressiveness and efficiency.
  • How graph models can enhance AI capabilities.


Challenges in Modernizing Engineering Workflows:

  • Issues with outdated check-in/check-out processes in PLM systems, especially with the integration of software and electromechanical designs.
  • The need for collaborative tools that allow engineers from different disciplines (mechanical, software, electrical) to work together seamlessly.


Emerging Trends for 2025:

  • The shift towards collaborative workspaces that leverage graph technology to manage product data dynamically.
  • The significance of generational differences in tech adoption—how younger professionals may prefer real-time collaboration methods over traditional file management.


The Future of Data Management in PLM:

  • Emphasis on the importance of contextualized data for AI applications.
  • The role of semantic technology in enhancing data interoperability across different systems and platforms.


All agree that while challenges remain, the future of digital products and manufacturing looks promising with advancements in graph technology and improved collaborative workflows set to redefine the industry landscape by 2025.

Share your questions, comments, or future topic suggestions.

Thank you for tuning in! Stay Sharp!

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