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

Authors: Pedro Vaz; Ana Cristina Braga; Maria do Sameiro Carvalho

Addresses: ALGORITMI Centre, University of Minho, 4800-058 Guimarães, Portugal ' ALGORITMI Centre, University of Minho, 4800-058 Guimarães, Portugal ' ALGORITMI Centre, University of Minho, 4800-058 Guimarães, Portugal

Abstract: 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.

Keywords: advanced statistical methods; ASMs; real-time industrial process analysis; advanced process control; process improvement; systematic literature review; SLR.

DOI: 10.1504/IJADS.2025.144818

International Journal of Applied Decision Sciences, 2025 Vol.18 No.2, pp.215 - 227

Received: 01 Apr 2023
Accepted: 27 Jun 2023
Published online: 03 Mar 2025 *

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