Arkansas Steel

Arkansas Steel faced a persistent process yield challenge, operating at 86% — a figure that, in steel manufacturing, translates directly into significant raw material waste, higher energy consumption per ton of finished product, and compressed margins. In the metals and mining sector, even small yield losses compound quickly at production scale: scrap and reprocessing costs erode profitability while increasing furnace load and cycle times. With commodity steel prices subject to market volatility, the inability to optimize yield through the existing process controls represented a structural cost disadvantage that could not be offset through pricing alone.

Arkansas Steel partnered with Rockwell Automation to deploy a process optimization solution targeting the core variables driving yield loss in its steelmaking operations. Rockwell Automation's FactoryTalk Analytics platform — specifically its advanced process control and analytics capabilities — was integrated with existing plant systems to model process parameters and identify the control adjustments needed to push yield higher. The implementation involved connecting to real-time process data streams, building predictive models around key metallurgical variables, and delivering operator guidance through the existing HMI infrastructure. This approach allowed Arkansas Steel to layer optimization capabilities onto its current automation architecture without a full system replacement, reducing deployment risk and accelerating time to value.

The optimization program delivered a measurable step-change in process performance. Arkansas Steel raised its process yield from 86% to 90% — a 4-percentage-point improvement that directly reduces raw material input required per ton of finished steel. In steelmaking, gains of this magnitude are significant: they translate to less scrap, lower reprocessing costs, and more saleable output from the same charge weight.

• Process yield: 86% → 90%
• Material efficiency: Higher yield per heat reduces waste and rework
• Profitability impact: Direct improvement in cost-per-ton economics without capital-intensive equipment changes

• Process optimization in steel manufacturing can deliver meaningful yield gains by targeting control parameters that operators cannot consistently manage manually at production speed.
• Integrating advanced analytics with existing automation infrastructure — rather than replacing it — allows faster deployment and lower implementation risk.
• A 4-point yield improvement in metals production has outsized financial impact because raw material and energy costs dominate the cost structure.
• Establishing clear baseline metrics (yield %, scrap rate) before deployment is essential for measuring and communicating ROI post-implementation.
• Vendor expertise in both industrial automation and analytics (as Rockwell Automation provides) matters when bridging OT data with optimization models.