Case Study: a top-10 automotive parts manufacturer cuts scrap and catches defects with StackAI

Top-10 Automotive Parts Manufacturer cuts defect review from hours to 2 minutes with Stack.ai

A top-10 automotive parts manufacturer faced significant challenges analyzing its production data to reduce costly scrap and defects. Manual reviews of spreadsheets were slow, preventing timely insights, and critical processes like curing adjustments were bottlenecked by scarce expert availability. The company engaged Stack.ai to explore using AI agents to automate these workflows without disrupting existing data collection systems.

Stack.ai implemented three AI agentic workflows to address these issues. A defect pattern analyst automated the detection of production issues from shift files, a press control agent provided real-time curing recommendations, and a procurement agent automated daily market and inventory analysis. These solutions turned hours of manual work into streamlined, minute-long reviews, enabling the company to catch defects faster, scale expert knowledge, and proactively manage procurement, significantly reducing scrap and operational delays.