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Title:
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A CONCEPT OF ENABLING DATA CONSISTENCY
CHECKS BETWEEN PRODUCTION AND PRODUCTION
PLANNING USING AI |
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Author(s):
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Emilia Gelwer, Jens Weber and Frederik S. Bäumer |
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ISBN:
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978-989-8704-24-5 |
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Editors:
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Hans Weghorn |
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Year:
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2020 |
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Edition:
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Single |
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Keywords:
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Artificial Intelligence, Anomaly Detection, Production Planning, Production, Data Consistency |
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Type:
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Short |
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First Page:
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139 |
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Last Page:
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142 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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A variety of methods and systems must be linked together to support production planning with insights from existing
production data. In this short paper, we give insight into our concept intended to show how malfunctions, occurring in
running production lines, can be analyzed with AI methods and made available to production planning. Using
IoT-enabled production systems, target and live data can be routed via a Manufacturing Service Bus to a data lake and
then evaluated on-the-fly using anomaly detection. Detected anomalies are then compared with existing maintenance
documentation from an existing ERP system to indicate malfunctions. Stored malfunctions are further evaluated via
Natural Language Processing and enriched with information from IoT-enabled production systems. Further analysis of
correlating parameters is carried out to store findings in a structured knowledge database to learn for the future from the
mistakes of the past. |
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