Intent-Driven Automata for Intent Structuring and Translation in Industry 4.0

This paper introduces Intent-Driven Automata (IDA), a comprehensive approach that systematically translates and validates high-level user intents into structured, executable system configurations. Our approach implements a three-layer validation architecture: syntactic verification through Extended Backus-Naur Form grammar parsing, semantic coherence validation via knowledge graph reasoning, and operational constraint enforcement using Finite State Machine transitions. We employ advanced natural language processing techniques for initial intent extraction, followed by formal grammar-based structuring and graph-based semantic verification. We evaluate our approach on a dataset of structured manufacturing intents and demonstrate its effectiveness in reducing validation inconsistencies while maintaining computational efficiency. The findings place IDA as an understandable solution for Industry 4.0 environments that bridges the gap between human-defined operational intents and their automated implementation in complex manufacturing environments.