Logo des Repositoriums

Künstliche Intelligenz 33(2) - Juni 2019

https://dl.gi.de/handle/20.500.12116/36216
Auflistung nach:

Auflistung Künstliche Intelligenz 33(2) - Juni 2019 nach Schlagwort "Edge Manufacturing"

1 - 1 von 1
  • Zeitschriftenartikel
    A Jumpstart Framework for Semantically Enhanced OPC-UA
    (KI - Künstliche Intelligenz: Vol. 33, No. 2, 2019) Katti, Badarinath; Plociennik, Christiane; Schweitzer, Michael
    Decentralization is the norm of future smart production as it assists in contextual dynamic decision-making and thereby increases the flexibility required to produce highly customized products. When manufacturing business software is operated as a cloud based solution, it experiences network latency and connectivity issues. To overcome these problems, the production control should be delegated to the manufacturing edge layer and hence, the argument of decentralization is even more applicable to this narrative. In order to accomplish the assigned manufacturing task effectively, the edge layer is required to possess contextual awareness to make run-time decisions in production. Semantic technologies, on the other hand, assist in discerning the meaning, reasoning and drawing inferences from the data. There are several specifications and frameworks to automate the discovery, orchestration and invocation of web services; the prominent are OWL-S, SAWSDL and WSMO. This paper derives a hybrid approach that integrates OWL-S and SAWSDL specifications to overcome the downsides, yet retain the benefits of both approaches to the OPC-UA application methods. Consequently, the proposed semantically enriched OPC-UA concept enables the edge layer to create flexible production orchestration plans in a manufacturing scenario controlled by cloud MES. Furthermore, the derived hybrid approach is applied to a real use case to demonstrate its feasibility in industrial environments.