@misc{13334,
  abstract     = {{Retrieval-augmented generation (RAG) based on large language models (LLMs) has established itself as a key technology for combining domain-specific information with generative language skills, thereby providing transparent, up-to-date information. Many firms are already piloting such LLM-based information systems, but report a high degree of complexity in planning and implementation. A generally accepted regulatory framework that consistently maps key decisions is not yet available to companies. This article therefore presents a multi-level system that organizes design decisions throughout the configuration process. This framework is intended to support users in the planning, realizing, evaluation, and further development of an LLM-based information system. To achieve this goal, a qualitative-empirical research design was chosen. First, publications from the period 2022 to 2025 were identified and selected using a systematic literature search in accordance with the PRISMA guideline. The selected publications were then evaluated using a qualitative content analysis. The result is a system that was reviewed, revised and finalized at an expert workshop.}},
  author       = {{Ullrich, Dominik and Wallys, Jens and Hinrichsen, Sven}},
  booktitle    = {{Intelligent Human Systems Integration (IHSI 2026): Disruptive and Innovative Technologies}},
  editor       = {{Ahram, Tareq and Karwowski, Waldemar and Giraldi , Laura and Benelli , Elisabetta}},
  isbn         = {{978-1-964867-76-2}},
  issn         = {{2771-0718}},
  keywords     = {{Retrieval-Augmented Generation, LLM-Based Information System, Conceptual Framework}},
  location     = {{Florence}},
  pages        = {{63--73}},
  publisher    = {{AHFE International}},
  title        = {{{Conceptual Framework for Designing Domain-Specific LLM-Based Information Systems}}},
  doi          = {{10.54941/ahfe1007065}},
  volume       = {{200}},
  year         = {{2026}},
}

@misc{13293,
  abstract     = {{The performance of large language models (LLMs) has improved significantly in recent years, with the result that they are now used in many companies in various industries. However, the design of a company-specific information system involving an LLM is associated with a large number of decisions. This leads to a high level of complexity in the design task. Against this background, companies need a structured approach that methodically supports the planning, development, implementation and long-term maintenance of LLM-based information systems so that domain- and company-specific requirements are taken into account as a result. This article therefore describes a method that supports the design, introduction and maintenance process of an LLM-based information system. The method consists of a process model and a list of design principles, which are also referred to as success factors. The process model developed is based on the proven six-stage REFA planning system. To identify and describe success factors, a systematic literature search was carried out. Based on an analysis of the contents of individual literature sources, success factors for the design of LLM-based information systems were identified. These success factors relate, for example, to the quality of the data provided, data security, user-centered system design and feedback mechanisms for improving information output.}},
  author       = {{Hinrichsen, Sven and Herbort, Robin and Green, Dominik and Adrian, Benjamin}},
  booktitle    = {{Human Interaction and Emerging Technologies (IHIET 2025)}},
  editor       = {{Ahram, Tareq and Motschnig, Renate }},
  isbn         = {{978-1-964867-73-1}},
  issn         = {{2771-0718}},
  keywords     = {{Large language model, Information system, Retrieval augmented generation}},
  location     = {{Vienna}},
  publisher    = {{AHFE}},
  title        = {{{How to Design an Operation-Specific LLM-Based Information System}}},
  doi          = {{10.54941/ahfe1006709}},
  volume       = {{197}},
  year         = {{2025}},
}

@article{4897,
  abstract     = {{Assistance is becoming increasingly relevant in carrying out industrial work in the context of cyber-physical production systems (CPPSs) and Industry 4.0. While assistance in a single task via a single interaction modality has been explored previously, crossdevice interaction could improve the quality of assistance, especially given the concurrent and distributed nature of work in CPPSs. In this paper, we present the theoretical foundations and implementation of MiWSICx (Middleware for Work Support in Industrial Contexts), a middleware that showcases how multiple interactive computing devices such as tablets, smartphones, augmented/virtual reality glasses, and wearables could be combined to provide crossdevice industrial assistance. Based on activity theory, MiWSICx models human work as activities combining multiple users, artifacts, and cyber-physical objects. MiWSICx is developed using the actor model for deployment on a variety of hardware alongside a CPPS to provide multiuser, crossdevice, multiactivity assistance.}},
  author       = {{Dhiman, Hitesh and Röcker, Carsten}},
  issn         = {{2288-4300 }},
  journal      = {{Journal of Computational Design and Engineering}},
  keywords     = {{human–technology interaction, human–computer interaction, crossdevice interaction, cyber-physical systems, assistance, smart factory, middleware, actor model, information system design, industry 4.0}},
  number       = {{1}},
  pages        = {{428--451}},
  publisher    = {{Oxford University Press}},
  title        = {{{Middleware for providing activity-driven assistance in cyber-physical production systems}}},
  doi          = {{10.1093/jcde/qwaa088}},
  volume       = {{8}},
  year         = {{2021}},
}