Overcoming Pain Points in Moldmaking with AI

The moldmaking industry faces several pain points that hinder efficiency and innovationas according to my recent discussion with Mike Murakami of StackTeck Systems. These challenges include time-consuming redundant tasks, limited access to shared industry knowledge and resistance to adopting new technologies due to traditional shop cultures. Fortunately, artificial intelligence (AI) offers practical solutions to address these issues, as demonstrated by Mike’s experience at StackTeck.

• Redundant Tasks: Take manually logging machine run times, for

  Another AI Integration Initiative

  Here is a "how to get started" approach in AI to tackle a challenging technical problem. Instead of discarding old electronics as e-waste, repurposed end-of-life equipment was used to connect legacy EDM machines to Stack Teck’s machine monitoring dashboard.

  

  Real-world AI prompting solves specific problems with ChatGPT/Copilot.

  Demonstrating Practical AI Applications: The project showcases real-world AI prompting and interaction using ChatGPT/Copilot, illustrating step-by-step problem-solving for a highly specific and tailored use case.

  Rethinking and quick turnarounds: By not relying on “off-the-shelf” solutions, StackTeck was able to test for viability on the same day, with nearly instant solutions provided by AI to address all roadblocks. The project highlights how AI was used not just as a technical companion but also provided a working roadmap and viable path to success.

  Sustainability Angle: Repurposing old devices prevents e-waste from entering landfills. Even if the technology is old, AI provides many clever workarounds to work with unsupported protocols, outdated languages, buggy interfaces, and known limitations.

  Adding functionality: The EDM machine in this example pre-dates a software-only solution for monitoring. When the features you want for a unified solution can’t be added through a software update, a nontraditional approach using AI was generated to unify all machines on the same platform.

  example, which consumes valuable time. By leveraging AI, he developed a dashboard that automatically aggregates EDM machine data, saving 10-15 minutes per employee per day. This efficiency gain allows workers to focus on higher-value tasks, boosting productivity across the department.
• Limited Knowledge Sharing: The industry suffers from “tribal knowledge” held by experienced workers, which is rarely documented. AI struggles with moldmaking’s niche data due to its limited presence in large datasets. Encouraging social media sharing and using AI to capture and organize this knowledge can bridge this gap, ensuring critical insights are preserved for future generations.
• Resistance to New Technology: Traditional shop cultures often resist change, viewing AI with skepticism. Open-minded environments, like StackTeck’s, foster innovation by encouraging experimentation with AI. Starting with simple projects, such as data management for part numbers, can demonstrate AI’s value and build buy-in among coworkers.

By addressing these pain points—redundant tasks, knowledge retention and cultural resistance—AI can help transform moldmaking. Shops that embrace AI as a tool, not a threat, can enhance efficiency, preserve expertise and attract tech-savvy talent.