AI-Supported Workflows for Chemical Batch Plants

Optimizing quality, efficiency and safety

Thema: KI

Publikationsform: Fachartikel
Artikelnummer: 03654_2020_08_04
Zeitschrift: AI-Supported Workflows for Chemical Batch Plants
Erscheinungsdatum: 11.08.2020
Autor: Martin Hollender, Benedikt Schmidt, Arzam Kotriwala, ABB Corporate Research Center Germany
Verlag: Vulkan-Verlag GmbH
Seiten: 9
Publikationsformat: PDF
Sprache: de
Themenbereich: Automatisierungstechnik

Details

This article presents an AI supported solution for cross-application workflows in batch plants. Based on a digital virtual assistant, industrial digital services are connected in workflows and support users in making the best use of the digital infrastructure. We focus on two digital services which allow for early detection of faults within the production and root cause analysis: a novel approach to online identification of batch failures building on an adjusted form of multiway principal component analysis and a low-cost sensing approach to perform root cause analysis for different failure modes occurring in batch plants. A case study of the implementation in a test plant is reported together with insights into the benefits and limitations of the approach gained via several process executions.

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