| Autor: |
Julian Weller, Nico Migenda, Yash Naik, Tim Heuwinkel, Arno Kühn, Martin Kohlhase, Wolfram Schenck, Roman Dumitrescu |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Mathematics, Vol 12, Iss 17, p 2663 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2227-7390 |
| DOI: |
10.3390/math12172663 |
| Popis: |
Prescriptive analytics plays an important role in decision making in smart factories by utilizing the available data to gain actionable insights. The planning, integration and development of such use cases still poses manifold challenges. Use cases are still being implemented as standalone versions; the existing IT-infrastructure is not fit for integrative bidirectional decision communication, and implementations only reach low technical readiness levels. We propose a reference architecture for the integration of prescriptive analytics use cases in smart factories. The method for the empirically grounded development of reference architectures by Galster and Avgeriou serves as a blueprint. Through the development and validation of a specific IoT-Factory use case, we demonstrate the efficacy of the proposed reference architecture. We expand the given reference architecture for one use case to the integration of a smart factory and its application to multiple use cases. Moreover, we identify the interdependency among multiple use cases within dynamic environments. Our prescriptive reference architecture provides a structured way to improve operational efficiency and optimize resource allocation. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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