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Advanced statistical methods for real-time industrial process analysis: an analysis of the literature

Pedro Vaz et al.

International Journal of Applied Decision Sciences2025https://doi.org/10.1504/ijads.2025.144818article
AJG 1
Weight
0.50

What the paper says

Real-time work and data-driven (DD) strategies are gaining popularity in Industry 4.0, which highlights the importance of revising the statistical methods applied in these environments. This study is the first systematic literature review on advanced statistical methods for real-time industrial process analysis (ASMs-RTIPA), offering valuable insights for future research by compiling existing recent studies (from 2014 to 2020) systematically. The review indicates a lack of publications on ASMs-RTIPA, yet it supports its application. Approximately 41% of the selected publications use case studies, 23% develop models, and 18% are conceptual. 'Advanced process control' is the most common keyword in the publications studied. The majority of publications come from the USA, UK, Germany, and the Netherlands. Engineering, generally, has the highest concentration of publications on the subject.

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https://doi.org/https://doi.org/10.1504/ijads.2025.144818

Or copy a formatted citation

@article{pedro2025,
  title        = {{Advanced statistical methods for real-time industrial process analysis: an analysis of the literature}},
  author       = {Pedro Vaz et al.},
  journal      = {International Journal of Applied Decision Sciences},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1504/ijads.2025.144818},
}

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Advanced statistical methods for real-time industrial process analysis: an analysis of the literature

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.