Full AI Autonomous Governance Factory (Full-AGF): Implementation Pathway of the Universal Production Line

Abstract

We propose a normatively verifiable construction pathway for the Universal Production Line (UPL), targeting equipment self-supply and prototyping during the factory-construction phase. The implementation line is as follows: the Manufacturing Digital Base (MDB) transduces the physical world into AI-operable digital assets; four categories of integration actions give rise to an autonomous simulation closed loop fed by collision logs, enabling action flows to be autonomously refined before ever running on the physical machine; capability is then verified progressively along the graduated ladder of “fixed flow → parameterized flow → autonomously orchestrated flow,” culminating in a universal production line that integrates three segments—circuitry, mechanisms, and fixed workstations. To render “full” autonomy decidable, we introduce four measurable admission criteria—full-chain closed loop, autonomous generation, autonomous verification, and autonomous governance—and instantiate them as collectable metrics with recommended acceptance thresholds (representative recommended values: first-pass rate (FPR) ≥ 95%, generation success rate (GSR) ≥ 90%, abnormal self-closure rate (ASCR) ≥ 80%, steady-state human intervention rate (HIR) ≤ 5%; all are suggested values pending calibration). The decision criterion is whether AI forms a complete closed loop covering the six links of sensing, drafting, interaction, simulation, decision-making, and execution, and autonomously governs its own operation—not whether AI technology is used. Throughout the paper, an evidence-boundary table explicitly separates constructed engineering prototypes from research agendas yet to be validated, and an end-to-end concept validation (PoC) protocol is provided. This paper is positioned as a definitional contribution and a research agenda, not as a claim of achieved full autonomy.