Transformations in manufacturing quality in the Industry 4.0 era: A semi-centennial review using latent Dirichlet allocation

  • Wala Abed Al Khader
  • , Raja Jayaraman
  • , Khaled Salah
  • , Jiju Antony
  • , Mohammad Omar

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

The rapid and ongoing developments in the quality and manufacturing sectors, fueled by digitalization, present significant challenges for manufacturers. These challenges, including meeting high-quality standards, customer expectations, regulatory compliance, and addressing environmental sustainability goals, underscore the need for a comprehensive exploration of quality in manufacturing and its evolution. In particular, the influence of the fourth industrial revolution serves as a central catalyst within these domains. This study offers a comprehensive semi-centennial review of literature from the Scopus database on quality in manufacturing, employing a Latent Dirichlet Allocation machine learning approach. The study encompasses 122,043 publications published predominantly between 1970 and 2023, utilizing bibliometric, textual, and temporal analyses. The analysis divides the timeline into pre-Industry 4.0 (up to 2011) and post-Industry 4.0 (2011 onward) periods, analyzing predominant research domains and assessing their evolution and impacts. Furthermore, the study explores shifts observed between these periods and provides futuristic insights into the era of digital transformation with implications for academia, industry, and policymaking.

Original languageBritish English
Article number111340
JournalComputers and Industrial Engineering
Volume208
DOIs
StatePublished - Oct 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  2. SDG 17 - Partnerships for the Goals
    SDG 17 Partnerships for the Goals

Keywords

  • Industry 4.0
  • LDA
  • Manufacturing
  • Quality
  • Topic modeling

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