Case Study: Large Aluminum Manufacturing Company achieves higher aluminum yields, lower energy consumption and faster KPI analysis with Statistica

Large Aluminum Manufacturing Company - Customer Case Study

A North American aluminum manufacturer (about 1,000 employees) faced a challenge: complex smelting processes with 15–50 interacting daily variables made it difficult and time-consuming to pinpoint why production yields fluctuated. Engineers needed a way to move from slow, weekly analyses to real-time, precise control of factors like temperature, cell voltage and stability to increase yield and cut energy use.

The company implemented Statistica predictive analytics and multivariate SPC, using automated models and neural networks to identify, predict and control the variables that drive performance. The solution cut KPI analysis time by ~25%, increased overall aluminum yield, improved visibility into process drivers, reduced energy consumption and greenhouse gas emissions, and enabled standardized, automated practices that boosted productivity and cost-efficiency.