Exploring statistical and machine learning methods for modeling probability distribution parameters in downtime length analysis: a paper manufacturing machine case study

Exploring statistical and machine learning methods for modeling probability distribution parameters in downtime length analysis: a paper manufacturing machine case study

Abstract Manufacturing companies focus on improving productivity, reducing costs, and aligning performance metrics with strategic objectives. In industries like paper manufacturing, minimizing equipment downtime is essential for maintaining high throughput. Leveraging the extensive data generated by...

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Bibliographic Details
Main Authors: Vladimir Koković, Kosta Pavlović, Andjela Mijanović, Slavko Kovačević, Ivan Mačužić, Vladimir Božović
Format: Article
Language:English
Published: SpringerOpen 2024-11-01
Series:Journal of Big Data
Subjects:
Lean industrial systems
Paper manufacturing
Production downtime
Big data analytics
Machine learning
Unsupervised learning
Online Access:https://doi.org/10.1186/s40537-024-01030-4
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https://doi.org/10.1186/s40537-024-01030-4

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