May 2026 Volume 8

AUTOMATION

TEACHING ROBOTS How Automated Grinding Is Redefining Finishing in Steelmaking By Chad Lacher, Damon Schnieder, and Jeffery Clay

From Manual Variability to Robotic Repeatability

In the legacy process, ultrasonic and surface inspection systems identified surface imperfections and marked bars with paint. Operators then searched visually for those painted markers and then performed exploratory grinding. This approach was dependent on visibility, accuracy of paint application, and human perseverance for repetitive tasks. The new automated system replaces that uncertainty with a direct data link. Inspection data is transmitted digitally to the robots, which orient each bar precisely and grind exactly where the data indicates. This one-to-one integration removes an entire layer of potential error and reduces waste, while accelerating processing time from hours per bar to minutes. The result is a more uniform surface finish that exposes potential surface conditions, enabling operators to verify quality with greater clarity and confidence. Teaching the Robot to Grind Like a Pro Early customer feedback revealed an important nuance: robots were too good at their jobs! Their initial programming removed material so precisely and thoroughly that distinct grind transitions, or steps, now appeared on finished product. Previously, an experienced employee would have instinctively feathered or tapered the product to avoid noticeable transition lips. Left unaddressed, these transitions could become downstream defects during forging or forming. Rather than viewing this as a setback, the team treated it as a refinement opportunity. Engineers reprogrammed the robotic paths to mimic the “artisan” touch of experienced operators, blending consistency with subtle variation. The outcome preserved downstream performance while maintaining the repeatability that only automation can deliver.

M anufacturers have long been processes such as steelmaking. While automation has many advantages, it succeeds not when it replaces people, but when it removes them from risk while best utilizing their expertise. Metallus, an Ohio-based manufacturer of specialty metals, applies this philosophy across its operations. It guided the development of Metallus’ Automated Grinding Line (AGL) - a robotics‑driven system designed to improve safety, consistency, and throughput while delivering measurable value to customers in the special bar quality and seamless mechanical tube markets. The Business Case: Safety First, Consistency Always The original motivation for automation was straightforward. Manual grinding exposed operators to fatigue, repetitive motion, heat, and airborne particulates while asked how automation is shaping more traditional manufacturing

requiring hours of continuous physical effort on individual bars. These conditions created safety hazards and introduced natural variability into the finishing process. By shifting some grinding to robotic cells, the company was able to minimize hazards while preserving their role in craftsmanship and quality. Operators were not eliminated; instead, they transitioned into higher-value working areas focused on inspection, process optimization, and quality control.

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