Data governance in smart factories: Consistency rules for improved data quality in logistics & operations

Smart factories are becoming a mine in the Big Data era. These plants and the connected supply chain are equipped with tons of sensors able to track the production and transportation processes. Nevertheless, all these data may lose their value without appropriate data governance and powerful quality...

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Bibliographic Details
Published in:Manufacturing letters 2023-09, Vol.37, p.57-60
Main Author: Tufano, A.
Format: Article
Language:English
Subjects:
Data governance
Data management
Data quality
Digital twin
Smart Factory
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Summary:Smart factories are becoming a mine in the Big Data era. These plants and the connected supply chain are equipped with tons of sensors able to track the production and transportation processes. Nevertheless, all these data may lose their value without appropriate data governance and powerful quality controls. This paper introduces an expanded role of data governance in smart factories by proposing the implementation of quality controls after the data collection by source systems (e.g. ERP, MES, WMS, PLM). Quality controls are based on an original mathematical model to check the consistency of the collected data. The model calculates three mathematical functions called Movements, Inventory and Productivity with data collected from different data sources and enables the identification of data inconsistencies and errors by verifying the mathematical relationships between these three functions.
ISSN:2213-8463
2213-8463
DOI:10.1016/j.mfglet.2023.07.019