Integrating Smart Production Planning into Smart Production

Vogel, T.; Gernhardt, B.; Hemmje, M.

Angol nyelvű Konferenciaközlemény (Könyvrészlet) Tudományos
    Industry 4.0 R&D is currently driving the emergence of Smart Production Environments (SPE) where the manufacturing of new products takes place very flexibly and dynamically in several steps and locations, possibly distributed all over the world. Companies involved in such smart productions act in highly competitive global markets and always have to find new ways to, e.g., cut costs by changing to the best providers, or enabling, e.g., tax savings, to stay competitive. This can only be achieved by using the fastest, most effective, efficient, and flexible distributed collaborative production processes. In this context, a Collaborative Adaptive Production Process Planning (CAPPP) can be supported by semantic product data management approaches enabling production-knowledge representation, utilization, curation, and archival as well as knowledge sharing, access, and reuse in many flexible and efficient ways. To support such scenarios, semantic representation of production knowledge integrated into a machine-readable process formalization is a key enabling factor for sharing such explicit knowledge resources in cloud-based production knowledge repositories. Our approach of Knowledge-Based Production Planning (KPP) introduces such a method and already provides a corresponding prototypical Proof-of-Concept implementation. In this way, it can not only be used in production planning but also, e.g., in Collaborative Manufacturing Change Management (CMCM) as well as, e.g., in Collaborative Assembly-, Logistics-and Layout Planning (CALLP) both building on the results of CAPPP. Therefore, a collaborative planning and optimization from mass to lot-size one production in a machine readable and processable representation will be possible. On the other hand, KPP knowledge can be shared to support other types of innovation, collaboration, and cocreation within a cloud-based semantic production knowledge repository. © 2020 IEEE.
    Hivatkozás stílusok: IEEEACMAPAChicagoHarvardCSLMásolásNyomtatás
    2023-12-04 16:59