Template-as-Ontology: Configurable Synthetic Data Infrastructure for Cross-Domain Manufacturing AI Validation
LLarge language model (LLM)-based AI agents deployed in manufacturing environments require populated, schema-correct data for validation, yet production MES data is proprietary, privacy-encumbered, and vendor-specific. This paper introduces the Template-as-Ontology principle: a single Python configuration module (700-770 lines, 45 validated exports) serves simultaneously as the specification for a time-stepped manufacturing simulator and as the runtime domain schema for AI analytics tools, produ
Record details
Published: 11 May 2026
Source: arXiv
Category: Research
Topics: Privacy · Agents & autonomy · Environment
Retrieved: 14 July 2026
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How to cite this record
ethics.ai (11 May 2026), “Template-as-Ontology: Configurable Synthetic Data Infrastructure for Cross-Domain Manufacturing AI Validation,” evidence record 4529, https://ethics.ai/record/4529 (originally published by arXiv).
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