AI and the Reshaping of Fastener Engineering
Executive summary Fasteners are cheap per unit, made in enormous volumes, and responsible for a disproportionate share of assembly failures, engineering change orders and non-conformance reports. That combination makes them a natural target for AI: small gains in defect detection, joint design or procurement compound across millions of parts. The sources reviewed point to five areas of change, at very different levels of maturity: Quality inspection is the most mature. Deep-learning vision is moving from pilot to product in optical sorting and high-speed inspection. Design and selection tools that read [...]