Requirements towards optimizing analytics in industrial processes

نویسندگان

چکیده

Modern production systems are composed of complex manufacturing processes with highly technology specific cause-effect relationships. Developments in sensor and computational science allow for data-driven decision making that facilitate effcient objective management. However, process data may only be beneficial if it is enriched meta information expertise, reduced to relevant modelling results interpreted correctly. The importance integration the heterogeneous industrial environment rises at same momentum as new metrology techniques deployed. In this paper, we focus on optimizing analytics, containing predictive quality maintenance. We summarize key requirements analytics machine learning application processes. With a use case from automotive component characterize production, categorize put context real-world example.

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ژورنال

عنوان ژورنال: Procedia Computer Science

سال: 2021

ISSN: ['1877-0509']

DOI: https://doi.org/10.1016/j.procs.2021.03.074