Manufacturing Data Fusion: A Case Study with Steel Rolling Processes

Andi Wang ()
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Andi Wang: Arizona State University

A chapter in Multimodal and Tensor Data Analytics for Industrial Systems Improvement, 2024, pp 281-295 from Springer

Abstract: Abstract Production systems typically generate massive sensing data. Data fusion methods are required to transform these sensing data into valuable knowledge for process and quality improvement. This chapter provides a summary of a series of studies motivated by steel rolling processes, which addresses several aspects, including estimating the effects of process operations, predictive modeling, and unsupervised event identifications.

Keywords: Production data analysis; Steel rolling processes (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-031-53092-0_13

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DOI: 10.1007/978-3-031-53092-0_13

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