Hinzmann, D.D.HinzmannHasselder, D.D.HasselderLezama, S.S.LezamaKirik, O.O.KirikPandey, V.V.PandeyBosler, E.E.BoslerSpitta, D.D.SpittaUhlmann, EckartEckartUhlmannKrüger, J.J.KrügerMarkl, V.V.MarklOberschmidt, D.D.OberschmidtRötting, M.M.Rötting2024-08-012024-08-012024https://publica.fraunhofer.de/handle/publica/47237210.1007/978-3-031-47394-4_62-s2.0-85178352664Artificial intelligence (AI) has already been the subject of extensive scientific and industrial research in order to solve current challenges in intelligent manufacturing. However, these approaches often do not yet reach industrial small and medium-sized enterprises (SMEs). To meet the demand for resilient and sustainable production processes, the aim is to develop concepts to transfer applications into cyber physical production systems. Therefore, AI methods can be introduced as part of a smart manufacturing chain. In this work, an infrastructure to efficiently handle production data which is independent of the individual production process such as machining, grinding or electrical discharge machining is presented. Subsequently, an exemplary roadmap for SMEs is given to establish AI applications within the scope of manufacturing industry 4.0. As a result, an increase in efficiency and profitability of individual production processes as well as the overall production chain can be achieved.enArtificial intelligencecyber physical systemsindustry 4.0smart manufacturingconference paper