Paper Number
ECIS2026-1882
Paper Type
SP
Abstract
Simulation is widely used in production planning and scheduling (PPS), but the modeling process itself remains under-supported: decisions about scope, detail, and trade-offs are rarely documented, and current uses of Artificial Intelligence (AI) largely automate tasks rather than support collaborative reasoning. Drawing on a systematic literature review of PPS simulation and insights from Human-AI Teams, this study develops the concept of a Simulation Task Manager (STM). Following a Design Science Research approach, we derive design goals and requirements and present an early prototype. The STM functions as an orchestration layer that structures the simulation workflow, makes roles and decisions explicit, and enables AI to participate as a collaborative assistant. The work contributes a human-centered artifact concept that enhances transparency and coordination in simulation modeling, supporting the shift toward Industry 5.0 practices.
Recommended Citation
Senjic, Pascal; Bitsch, Günter; and Braun, Prof. Dr.-Ing. Anja, "A Simulation Task Manager For Production Planning: Design Goals And Requirements For Human–Ai Teams" (2026). ECIS 2026 Proceedings. 3.
https://aisel.aisnet.org/ecis2026/entmodel/entmodel/3
A Simulation Task Manager For Production Planning: Design Goals And Requirements For Human–Ai Teams
Simulation is widely used in production planning and scheduling (PPS), but the modeling process itself remains under-supported: decisions about scope, detail, and trade-offs are rarely documented, and current uses of Artificial Intelligence (AI) largely automate tasks rather than support collaborative reasoning. Drawing on a systematic literature review of PPS simulation and insights from Human-AI Teams, this study develops the concept of a Simulation Task Manager (STM). Following a Design Science Research approach, we derive design goals and requirements and present an early prototype. The STM functions as an orchestration layer that structures the simulation workflow, makes roles and decisions explicit, and enables AI to participate as a collaborative assistant. The work contributes a human-centered artifact concept that enhances transparency and coordination in simulation modeling, supporting the shift toward Industry 5.0 practices.