AI evaluates threaded connections using torque, rotation measurements

ChangeBridge: Patent Apps - AI & Computing (G06N)

Published October 7th, 2024

Detected March 31st, 2026

Summary

USPTO published patent application US20260087405A1 for a method and apparatus using artificial intelligence to evaluate threaded connections based on torque and rotation measurements. The invention involves two AI systems where model parameters can be transmitted between them, enabling quality prediction even when the systems are not in communication. Inventors: Rainer RUEHMANN, Benjamin SACHTLEBEN, David GEISSLER.

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What changed

The patent application discloses a method and apparatus for evaluating threaded connections using machine learning. The system includes a first AI trained to predict threaded connection quality and a second AI configured to receive model parameters from the first AI, allowing quality prediction to continue when the two systems are disconnected. Key technical elements include transmitting model parameters between AI systems and using torque and rotation measurements as inputs for quality assessment.\n\nThis is a patent application publication, not a regulatory requirement. It does not create compliance obligations or deadlines. Companies developing AI systems for industrial quality control applications may wish to review for potential intellectual property considerations. No action is required for regulatory compliance purposes.

Source document (simplified)

← USPTO Patent Applications

THREADED CONNECTION EVALUATION WITH MACHINE LEARNING

Application US20260087405A1 Kind: A1 Mar 26, 2026

Inventors

Rainer RUEHMANN, Benjamin SACHTLEBEN, David GEISSLER

Abstract

A method for evaluating threaded connections can include transmitting model parameters from one artificial intelligence to another intelligence, inputting torque and rotation measurements to the second artificial intelligence, and updating the first artificial intelligence using data transmitted from a job location. An apparatus for evaluating threaded connections can include a first artificial intelligence trained to predict threaded connection quality, and a second artificial intelligence configured to receive model parameters from the first artificial intelligence, the second artificial intelligence being configured to predict threaded connection quality while the second artificial intelligence is not in communication with the first artificial intelligence.