Joschka Kersting, Gesa A. Benndorf · 2026 · IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)
DOI: 10.1109/etfa68377.2026.11725227 · cited by 0 works (OpenAlex) · open-access PDF
프로그래밍 가능한 논리 컨트롤러(PLC) 코딩은 문서, 프로젝트 파일 및 코드 편집자 간의 지속적인 컨텍스트 전환을 요구하는 수동적이고 IDE 중심적인 작업으로 남아있다. 최근의 작업은 탐색 증진된 대형 언어 모델이 높은 컴파일율로 공급자 준수한 구조화된 텍스트를 생성할 수 있다는 것을 보여주었지만, 이 시스템들은 코드 생성을 단일 파이프라인으로 취급합니다: 엔지니어는 쿼리를 제출하고 특정 공장에 대한 지속적인 지식이없는 코드를 수신합니다. 우리는 플랜트 인식 대화 콜포트를 제시하여이 패러다임을 세 가지 방향으로 확장합니다 : 플랜트 특정 컨텍스트 섭취, 설명 및 디버
Machine translation (Meta M2M100); the English original follows.
Programmable Logic Controller (PLC) coding remains a manual, IDE-centric task that demands constant context switching between documentation, project files, and code editors. Recent work has demonstrated that retrieval-augmented large language models can generate vendor-compliant Structured Text at high compilation rates \cite{pred}, yet these systems treat code generation as a one-shot pipeline: the engineer submits a query and receives code, with no persistent knowledge of the specific plant. We present a plant-aware conversational copilot that extends this paradigm in three directions: plant-specific context ingestion, a chat-first interaction model for explanation and debugging, and a graduated tool-access ladder from chat to deployment. The system is designed for real plant infrastructure and keeps the engineer in control of each step that produces real-world effects.
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Topics: Computer science, Code (set theory), Programmable logic controller, Generator (circuit theory), Code generation, Programming language
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