Engineering teams meticulously document component details but often fail to apply the same rigor to assembly specifications. This oversight becomes a major source of failure, especially when transitioning from pilot lines to high-volume manufacturing.

True AI design optimization is a multi-objective problem that must include manufacturing constraints from the outset. Rather than creating theoretically perfect but unbuildable parts, effective systems embed rules for processes like stamping, ensuring every generated design is viable for production.

Design for Excellence goes beyond just manufacturing costs. Consider the entire product lifecycle, including serviceability. A design that's easy to assemble but difficult to service in the field (like using a blind screw on a replaceable part) increases the total cost of ownership and harms the customer experience.

A key lesson from SpaceX is its aggressive design philosophy of questioning every requirement to delete parts and processes. Every component removed also removes a potential failure mode, simplifies the system, and speeds up assembly. This simple but powerful principle is core to building reliable and efficient hardware.

Designers should consider the human operators and machines that will assemble their product. By making choices that simplify manufacturing—providing clear instructions and avoiding known difficulties—the process becomes smoother and more efficient, akin to 'riding a bike downhill.'

A common Design for Manufacturability (DFM) error is specifying features like tiny chamfers or internal cuts that look feasible when a part is magnified on a CAD screen. In reality, these features are often physically impossible for a tool to access or create, necessitating direct communication with the machinist.

To ensure a smooth transition from development to production, an operations or manufacturing SME must be part of the design process from the start. Otherwise, products are developed without manufacturability in mind, leading to expensive, reactive fixes and subjective quality control during scale-up.

The default instinct is to solve problems by adding features and complexity. A more effective design process is to envision an ideal, complex solution and then systematically subtract elements, simplify components, and replace custom parts. This leads to more elegant, robust, and manufacturable products.

At American Housing Corp, engineers who design components also manufacture them in the factory and assemble them in the field. This forces them to experience the "pain" of their design decisions firsthand, creating a rapid, visceral feedback loop that leads to faster and more effective product improvements.