Case Study: Ford Motor Company achieves 90%+ stamping process selection accuracy and triples throughput with Altair Knowledge Works

Altair® Knowledge Studio® Speeds Stamping Process Selection, Increasing First-time-through Rates

Ford Mexico, part of Ford Motor Company, faced a time-consuming, expert-dependent challenge in selecting the optimal sheet-metal stamping process for thousands of part designs. With complex combinations of materials, thicknesses, and press options—and industry-average material utilization around 60%—the company sought to capture five years of production knowledge to reduce trial-and-error, scrap, and ramp-up time for new staff.

Working with Altair, Ford used Knowledge Studio to train machine-learning models on over 3,000 documented stamping runs; a decision-tree model achieved over 90% accuracy and, when combined with multiple datapoints, produced nearly perfect selections for many cases. The automated process selection tripled projected throughput, increased first-time-through rates, reduced rework time without adding resources, and sped up training by embedding Ford’s domain knowledge in the model.

Ford Motor Company