Autor: Malte Stonis

The increasing automation of intralogistics requires flexible and resilient control concepts for Autonomous Mobile Robots (AMR). While centralized coordination approaches enable stringent control, they quickly reach their limits in terms of scalability and robustness. This paper therefore presents regulations for the decentralized coordination of AMR within the framework of the ORPHEUS project. The focus is on translating known decentralized decision-making principles into a rule framework tailored to industrial material flow scenarios, addressing both operational task assignment and safety-related conflict situations. ORPHEUS thus makes a significant contribution to the methodological structuring, parameterization, and practical transferability of decentralized coordination logics.

Machine learning offers a wide range of potential, especially in production, and is therefore becoming increasingly important. However, small and medium-sized businesses are lacking guidelines that are specifically tailored to their individual challenges to guide them step-by-step through the process. In conjunction with a potential analysis, the determination of relevant prerequisites and a maturity assessment, this article can serve as a guide for SMEs.

The realization of reorganization projects represents a complex and independent planning task within the framework of factory layout planning. Only little methodical knowledge exists, which considers the temporal, spatial and organizational restrictions in the creation of a schedule. This paper aims to present the interdependencies in the planning and execution of realization projects and thus to provide a basis for discussion for further investigations in the field of scheduling factory relocations for the reorganization of factory objects.