Case Study: Aluminum Manufacturing Company achieves higher production, reduced energy consumption, and faster analytics with TIBCO Software

Aluminum Maker Crunches Big Data for Top Performance

A 900‑employee primary aluminum manufacturer needed to define productivity at the daily, per‑cell (batch) level but faced 15–50 interacting variables (cell voltage, stability, structure, etc.) that previously required weeks of analysis and prevented real‑time response. The team’s challenge was to capture and analyze these factors quickly enough to predict and control daily outcomes rather than relying on monthly adjustments.

The company deployed TIBCO Statistica predictive analytics with multivariate SPC and automated modeling (including neural networks) to monitor KPIs and predict the interplay of variables. The result: analysis time fell by about 25%, yields and total aluminum production rose, energy use was optimized (potentially ~5% savings), engineers gained greater visibility into hidden drivers, and the plant now detects and resolves issues faster—saving the company millions annually and boosting R&D and operational performance.