---
res:
  bibo_abstract:
  - The application of Large Language Models (LLMs) for the automated generation of
    assembly instructions shows significant potential for improving work preparation
    in production processes. However, challenges remain regarding the overall information
    quality and precision of the generated instructions. In light of these challenges,
    this study explores how the information quality of automatically generated assembly
    instructions can be enhanced through the targeted provision of structured input
    data, such as Assembly and Quantity BOMs (Bills of Materials), as well as the
    use of optimized prompt chaining techniques. The methodology employs ChatGPT-4o
    in combination with Retrieval Augmented Generation (RAG) within the Microsoft
    Azure environment. The results demonstrate that structured data inputs, particularly
    the use of Assembly BOMs with defined Tool-to-Component relations, significantly
    improve the precision and relevance of the generated instructions. Despite these
    advancements, achieving consistent information quality remains a barrier to broader
    practical implementation. Therefore, feedback loops should be integrated into
    the assembly instruction generation process to ensure continuous refinement and
    reliability. Future research should investigate the use of RAG or similar frameworks,
    focusing on optimizing data structures and implementing feedback mechanisms to
    enhance the automated generation of assembly instructions.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Robin
      foaf_name: Herbort, Robin
      foaf_surname: Herbort
      foaf_workInfoHomepage: http://www.librecat.org/personId=86239
  - foaf_Person:
      foaf_givenName: Dominik
      foaf_name: Green, Dominik
      foaf_surname: Green
      foaf_workInfoHomepage: http://www.librecat.org/personId=85489
  - foaf_Person:
      foaf_givenName: Sven
      foaf_name: Hinrichsen, Sven
      foaf_surname: Hinrichsen
      foaf_workInfoHomepage: http://www.librecat.org/personId=49010
  bibo_doi: 10.54941/ahfe1005883
  bibo_volume: 160
  dct_date: 2025^xs_gYear
  dct_isPartOf:
  - http://id.crossref.org/issn/2771-0718
  - http://id.crossref.org/issn/978-1-964867-36-6
  dct_language: eng
  dct_publisher: AHFE @
  dct_subject:
  - Assembly Instruction
  - Retrieval Augmented Generation (RAG)
  - Large Language Model (LLM)
  dct_title: Automatic Creation of Assembly Instructions by Using Retrieval Augmented
    Generation@
...