Chemical plants are engineered to yield high output, while also complying to regulations. In initial R&D phases, experts gather large amounts of information to ensure an optimal design. Here, the influence of the optimization of the process on planning and operation of the plant is important. However, during operation of the facility, little of the information required for R&D work is available in electronic and interoperable form. It is described how this challenge can be overcome by a systematic data integration approach using international standards, centered around the DEXPI working group.
Current methods of artificial intelligence may often proof ineffective in the process industry, usually because of insufficient data availability. In this contribution, we investigate how data standards can contribute to fulfill the data availability requirements of machine learning methods. We give an overview of AI use cases relevant in the process industry, name related requirements and discuss known standards in the context of implicit vs. explicit data. We conclude with a roadmap sketching how to bring the results of this contribution into practical application.
DEXPI – eine Initiative der drei großen Prozessindustrieunternehmen BASF, Bayer Technology Services und Evonik – will endlich das Kompatibilitätsproblem von CAE-Applikationen lösen. DEXPI (Data Exchange in the Process Industry) arbeitet dabei zusammen mit den führenden internationalen CAE-Firmen, der internationalen ISO-Community und Forschungseinrichtungen an Lösungen auf Basis der ISO 15926. Der erste große Meilenstein – der komplette, intelligente R&I-Austausch – ist nun greifbar nahe: Alle notwendigen Konzepte und Implementierungen basierend auf ISO 15926 liegen vor. Die CAE-Firmen arbeiten intensiv an entsprechenden Export- und Importschnittstellen. Ein erstes Software-Release ist für Anfang 2016 angekündigt.
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