Case study
Advanced Analytics Breakthrough Lets Metals Company Optimize Yield Cost
A new tool allows operators to find the most cost-effective blend to achieve a desired grade.
Case study
A new tool allows operators to find the most cost-effective blend to achieve a desired grade.
Over the course of about 12 weeks, we helped a producer of specialty metals develop a new tool that allows operators to optimize yield cost. Powered by advanced analytics, the tool has resulted in significant annual savings for the company.
Before our engagement, MetalCo’s furnace production managers had little access to data-driven insights that would help them improve yields. Product quality could vary depending on the complex interplay of up to eight ingredients, and production cost fluctuated with blend choices and market prices.
Working in close collaboration with MetalCo production managers, we trained and tested more than 10 predictive and simulation models to accurately forecast the future metal grade and its cost based on inputs and process conditions. Data collected from across MetalCo’s operations brought more than 250 variables into the analysis, which was linked to key process steps on an hourly basis.
The tool we delivered recommends the ideal recipe for any grade specification, under various raw materials and energy cost scenarios. In addition, a user-friendly dashboard allows furnace operators to compare historical blend performance for easy reference.