How Industry 4.0, artificial intelligence and augmented reality can boost Digital Lean Six Sigma

The impact of Industry 4.0 (I4.0) and its enabling technologies in the Lean Six Sigma (LSS) approach have been widely discussed by practitioners and researchers in the last decade. However, current literature still lacks consistent knowledge about the joint application of I4.0, Artificial Intelligen...

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Bibliographic Details
Published inTotal Quality Management & Business Excellence Vol. 35; no. 13-14; pp. 1542 - 1566
Main Authors Endrigo Sordan, Juliano, Andersson, Roy, Antony, Jiju, Lopes Pimenta, Marcio, Oprime, Pedro Carlos
Format Journal Article Book Review
LanguageEnglish
Published Abingdon Routledge 02.10.2024
Taylor & Francis Ltd
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Summary:The impact of Industry 4.0 (I4.0) and its enabling technologies in the Lean Six Sigma (LSS) approach have been widely discussed by practitioners and researchers in the last decade. However, current literature still lacks consistent knowledge about the joint application of I4.0, Artificial Intelligence (AI) and Augmented Reality (AR) in the context of LSS practices. It is expected that the symbiosis between these technologies and methods can generate new applications in the field of operational excellence. This study provides a theoretical landscape of how I4.0, AI and AR can boost digital LSS. A Systematic Literature Review (SLR) was conducted using articles published from 2011 to 2022 in the Web of Science and Scopus databases. In addition to the quantitative analysis performed with 313 selected articles, a thematic analysis covering 31 empirical works provides examples regarding how I4.0, AI and AR technologies can singularly support LSS practices. The SLR exposed trends on the research topics, the main thematic areas, and empirical evidence regarding how I4.0, AI and AR technologies have supported LSS practices. This study can help practitioners identifying new applications of I4.0 technologies and AI algorithms in order to expand the traditional toolbox and methods used in LSS.
ISSN:1478-3363
1478-3371
1478-3371
DOI:10.1080/14783363.2024.2375299