Forged Path Automation | We are process engineers, not just robot integrators — Landrum, SC
Forged Path Automation designs, builds, and supports turnkey robotic finishing and cleaning cells from Landrum, South Carolina, for manufacturers in the gas turbine, aerospace, and automotive industries.
The hardest problem in industrial robotics is not motion. It is knowing what to do when the part is not where the program expects it. NIST makes the point directly in its Agility Performance of Robotic Systems project, updated in April 2026: manufacturing robots are held back by long changeover times and limited reusability, and many high-precision robotic systems cannot adapt on their own to variation from one component or lot to the next.
NIST also observes that re-tasking a robot for a new job frequently takes an order of magnitude longer to program than doing the job by hand would take. For a shop running one part at high volume, that cost is paid once. For a shop running turbine airfoils that differ part to part, it gets paid again and again.
That difference sits behind the choice facing anyone specifying a finishing cell: fixed programming, or adaptive robot path planning.
Fixed programming: what it is, and where it wins
A fixed program is a taught or offline-generated path the robot repeats. The geometry is assumed. The fixture is assumed to place the part the same way on each load.
That approach costs less to build, stays simpler to support, and hands over to a maintenance team more easily. Where the part geometry is stable, the fixture is rigid, and the volume is high, fixed programming is the correct engineering answer. Reaching for sensing and adaptation on a part that does not vary buys cost and failure modes for no return.
Adaptive robot path planning: what changes
Adaptive robot path planning inverts the assumption. The cell measures the part it actually has — through vision, laser scanning, probing, or force feedback — and generates or modifies the path from that measurement.
Sensing locates the part and characterizes its condition. Software compares the measurement against the nominal model. The path is built or offset from the difference. Force control holds the media against the surface as found, rather than where the model places it.
Why turbine airfoils push toward the adaptive side
Turbine hot-section hardware is unforgiving of removal error. The Department of Energy’s Advanced Turbine Systems program, launched in 1992, produced single-crystal turbine blades and thermal barrier coatings able to survive firing temperatures pushed to 2,600 degrees Fahrenheit. Those materials and coating stacks define what a finishing operation is allowed to touch.
Add the variability of the parts themselves — casting tolerance on new hardware, service condition on repaired hardware coming through an overhaul shop — and a single taught path has to stay conservative enough to be safe on the worst case, which leaves work behind on the rest.
The middle ground most shops actually land in
The choice is rarely binary. A common arrangement runs a fixed nominal path with in-process correction layered on top: the robot knows roughly where the feature is, sensing supplies the offset, and force control absorbs what is left.
That hybrid costs less than full path regeneration and handles more variation than a taught path alone. It also carries its own requirement. Somebody has to decide how large a correction the cell may apply before it stops and flags the part, because a system that silently corrects for anything will happily grind a part that should have been rejected at incoming inspection.
How do you decide between fixed and adaptive robot path planning?
Fixed programming suits stable geometry, rigid fixturing, and high volume, where the part matches the model load after load. Adaptive robot path planning suits parts that vary — castings, repaired hardware, high-mix families — because the cell measures the part before building the path. The deciding question is how much the part changes between loads.
Neither approach survives a vague specification. A measurement has to be defined before a path can be built from it: what gets measured, against what reference, to what resolution, and what the cell does when the reading falls outside the expected band. That definition is the work a process study does before any cell is designed.
NIST frames the underlying questions well. What does the robot need to know, when does it need to know it, how will it get that knowledge, and how should the system respond when the knowledge differs from what was expected. A shop able to answer those four about its own parts already knows which side of this comparison it belongs on.
Forged Path Automation: Vision-Guided Robotic Finishing Built in Landrum, SC
Forged Path Automation was founded by process engineers who kept seeing the same problem: automation providers selling equipment without owning the process. We handle system design, tooling, build, programming, installation, training, and support under one contract.
Our Services Include:
- Technology and Partnerships — Roboticom path-planning and simulation software, and no-code programming
- Process Engineering and System Design — Studying the process first, then designing the cell around it
Have a finishing operation that’s hard to staff? Talk to a process engineer about the part, the volume, and the finish you need.
About the Author
Chris Urban is the Founder of Forged Path Automation. His 26+ year manufacturing career spans from an international manufacturing specialist trained in Zurich, Switzerland, to corporate President and business owner. Before launching Forged Path Automation (FPA), Chris scaled an industrial gas turbine business unit from its infancy to $50M in value, directed the zero-downtime relocation of 100+ industrial machines to a 150,000 sq. ft. Center of Excellence, and led US operations for a $2.3B global firm. Today, Chris leverages his deep technical roots and an MBA to engineer turnkey robotic finishing cells that deliver total production stability and clear ROI for high-mix manufacturers. Chris holds an advanced background in both the technical and financial sides of manufacturing, combining studies in Applied Science with a Master of Business Administration.
Connect with Chris on LinkedIn to talk shop or discuss your floor’s ROI.
Follow Forged Path Automation on LinkedIn or visit ForgedPathAutomation.com.
Works Cited
“Agility Performance of Robotic Systems.” National Institute of Standards and Technology, 24 Apr. 2026, www.nist.gov/programs-projects/agility-performance-robotic-systems.
“DOE Technology Successes — Breakthrough Gas Turbines.” U.S. Department of Energy, Hydrocarbons and Geothermal Energy Office, www.energy.gov/hgeo/doe-technology-successes-breakthrough-gas-turbines.