Practical articles on integrating AI into mechanical engineering workflows. Filter by category or search for specific topics.
How an HVAC manufacturer used AI surrogate models to reduce their CFD simulation times from days to minutes, enabling real-time design iteration.
A deep dive into how a mid-sized automotive supplier used generative design to reduce the weight of a critical suspension component by 22% while maintaining structural integrity.
A breakdown of the current AI tools available in major CAD packages and how to separate the marketing hype from practical engineering utility.
Stop asking 'What can AI do?' and start asking 'What do I wish I didn't have to do?' Learn how to build micro-tools that automate the 80% of your engineering workflows that drain your energy.
Your manager doesn't care about neural networks. Here's how to build a business case for AI adoption that speaks the language of ROI, risk mitigation, and competitive advantage.
Generative design has evolved from a buzzword to a practical tool. Here is how mechanical engineers can integrate AI-driven CAD into their daily corporate workflows.
From debugging GD&T callouts to generating Python scripts for data processing, here are the prompts that have become part of my daily engineering toolkit.
Stop spending hours copying and pasting plots into Word documents. Learn how to use Python and LLMs to generate comprehensive FEA reports automatically.
A real-world look at how one automotive supplier integrated AI-driven simulation and generative design into their product development process, and the organizational challenges they overcame.
You don't need to become a software developer. Here are the five Python libraries that will cover 90% of your engineering automation needs.
How machine learning models are moving from the server room to the factory floor, predicting failures before they happen and optimizing spare parts inventory.