August 2025 Volume 7

FORGING RESEARCH

A FORGING TECHNOLOGY FIRST INTEGRATING INDUSTRY 4.0 INTO AN AUTONOMOUS CNC FORGING MACHINE By Alex Bandar, Brian Thurston, Glenn Daehn, Mike Groeber, Colton Wright, Nate Bianco, & Samantha Trzinski

O ver the past 75 years, U.S. manufacturing has made the forging industry has experienced fewer visible advancements during the same period in which CNC machining and Additive Manufacturing have rapidly evolved. This discrepancy is due in part to the higher capital investment required and to the unique technical challenges inherent in forging. Although forging is one of the oldest manufacturing processes, issues such as limited process visibility during forging (what is called the "black box" phenomena), complex material behavior and underdeveloped predictive capabilities have resulted in less innovation in forging than in other metals manufacturing industries. Much has been said about applying Industry 4.0 principles to forging as a pathway to long-overdue progress. While certain technologies—sensors, automation and AI —have improved individual steps in the forging process, a fully integrated, transformative leap that brings together all these techniques has remained elusive, until now. Metamorphic manufacturing stands apart from subtractive manufacturing (i.e., CNC machining) and additive manufacturing (i.e., 3D metal printing) in a key way: it transforms the shape of solid metal into a final part without removing material or adding layers. This process is inherently more energy efficient than additive manufacturing, which requires stock metal to be melted and solidified, or powderized and sintered for each part. It also avoids the material waste associated with machining, which can involve buy-to-fly ratios greater than 10-to-1. However, the path to realizing practical metamorphic manufacturing—sometimes described as “CNC forging” or “robotic blacksmithing”—presents challenges that are arguably more complex than those faced by CNC or additive manufacturing. To address these challenges, the National Science Foundation (NSF) has funded a multi-year, multi-institutional Engineering Research Center (ERC) initiative known as NSF HAMMER-ERC . HAMMER stands for Hybrid Autonomous Manufacturing - Moving from Evolution to Revolution , and it represents the first comprehensive effort to unify sensors, automation, AI and more into a single, integrated manufacturing platform. Led by The Ohio State University, the NSF HAMMER-ERC includes four additional core academic partners—Northwestern University, Case Western Reserve University, the University of Tennessee Knoxville, and North Carolina Agricultural and Technical State University—along with dozens of industry collaborators and trade associations. Now in year four of a 10-year, $52 million program, the ERC has already delivered a number of practical breakthroughs in metal forming, the most prominent being the Agility Forge. significant strides in production technologies such as CNC machining and additive manufacturing. Despite this fact,

The Agility Forge is an autonomous robotic platform that transforms metal stock into final shaped parts without human intervention (Figure 1). By leveraging what we call the STARC platform — sensors, thermal control, actuators, robotics and computation— we bring Industry 4.0 technologies directly into the forging process. Our own algorithms analyze target geometries and automatically determine the sequence of heats and

Figure 1: Schematic of the Agility Forge.

deformation blows needed to form a part from a given workpiece. Subsequent figures provide examples of individual technologies applied to achieve CNC forging. We have developed our own software that can identify the thermomechanical process path (e.g., heating, tool selection, beating, reheating, part translation and part rotation) to take an arbitrary incoming stock shape and forge it to a target geometry. The user can input a variety of tool options that are loadable into the tool changer (e.g., hammering, flattening, piercing and splitting), and let the software propose tool paths to provide a target shape. The user can then decide how close to final part geometry they would like the Agility Forge to form. If a final machining pass is required, then the user may select near-net shape. We plan to augment our software to add pre-forming or post forming processes such as pre-form cogging to achieve a target initial microstructure, or post-forging CNC machining to achieve a final surface finish, tolerance or heat treatment to achieve final properties. In this way, an integrated forming operating system will be developed. The first part will service primarily autonomous forging, and subsequent manufacturing processes will be added into the software to produce a holistic AI that can choose not just optimum parameters for a unit manufacturing process but also the optimum combination of manufacturing technologies to produce a part to match desired parameters - tolerances, properties, speed to delivery, cost (including tooling) and more. Figure 2 indicates how the software predicts individual blows with a variety of tooling options loaded into the tool changer for this process.

FIA MAGAZINE | AUGUST 2025 70