Gemcor Production Solutions delivers advanced factory integration with automated fastening systems under Ascent Aerospace

Since 1937, Gemcor Production Solutions has been integral to the manufacturing process of aerostructures worldwide. Under Ascent Aerospace, Gemcor continues its tradition of producing industry leading solutions, evident in its latest award for a blue-chip commercial aircraft manufacturer. New product offerings take advantage of the latest technologies to support machine learning and lights-out functionality while capturing the value of implementing a digital twin.

"Enhanced visual quality inspection with machine learning capabilities, built-in cycle time optimization, and lights-out operations are just a few benefits of Gemcor's latest offerings," shared Michael Hinckley, Director of Strategic Programs at Ascent Aerospace. "These advancements allow our customers to ramp up production and save on costs, with zero compromise on quality. Our customers trust the legacy capabilities of Gemcor. The integration into Ascent Aerospace has not only solidified the brand but enhanced overall capabilities."

Ascent is continuously adapting Gemcor to meet customers' needs as technology advances. "From process engineering to build and installation, our process is to work closely with customers to develop their projects to ensure we are providing an advanced, efficient and cost-effective solution."

Gemcor Production Solutions features:

- All electric drill/fasten – any combination of aluminum, titanium, honeycomb, composite & steel

- - Cycle time optimization, achieving 21 fasteners per minute under full sensor control

- Use of adaptive control to optimize production settings within a user-friendly dashboard

- Siemens' SINUMERIK solution controller for enhanced controls architecture

- Digital twin solution utilizing a Siemens' environment

- Process control enhancements include fastener verification, sealant optimization, edge and feature detection for resync

- Debris & chip detection

- Machine learning to improve quality control & predictive maintenance for reliability