arXiv Machine Learning September 22, 2026 By Zhengyang (Cissy), Gu, Thomas Cook, Fredaljohn Rohrbaugh, Joseph E. Hernandez, Chris Couch

Autonomous Model Lifecycle Management for Digital Twin-Based Manufacturing Control

Read the original on arXiv Machine Learning →

The paper introduces a closed‑loop cyber‑physical system for autonomous model lifecycle management in automotive manufacturing, deployed since 2023. It manages paired physics and reinforcement‑learning models, selecting the best candidate through competitive retraining cycles and a Conductor orchestrator that handles plant‑wide inventories and fallback controls. The system incorporates an operator‑trust gate that rejects 23% of policies that deviate from established practice, achieving 28‑45% process stability improvements with no safety incidents.

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