Are Metaverse applications in Quality 4.0 enablers of manufacturing resiliency? An exploratory review under disruption impressions and future research

El Jaouhari, Asmae, Arif, Jabir, Samadhiya, Ashutosh, Kumar, Anil, Jain, Vranda and Agrawal, Rohit (2024) Are Metaverse applications in Quality 4.0 enablers of manufacturing resiliency? An exploratory review under disruption impressions and future research. The TQM Journal, 36 (6). pp. 1486-1525. ISSN 1754-2731


The purpose of this paper is to investigate, from a thorough review of the literature, the role of metaverse-based quality 4.0 (MV-based Q4.0) in achieving manufacturing resilience (MFGRES). Based on a categorization of MV-based Q4.0 enabler technologies and MFGRES antecedents, the paper provides a conceptual framework depicting the relationship between both areas while exploring existing knowledge in current literature.

The paper is structured as a comprehensive systematic literature review (SLR) at the intersection of MV-based Q4.0 and MFGRES fields. From the Scopus database up to 2023, a final sample of 182 papers is selected based on the inclusion/exclusion criteria that shape the knowledge base of the research.

In light of the classification of reviewed papers, the findings show that artificial intelligence is especially well suited to enhancing MFGRES. Whereas transparency and flexibility are the resilience enablers that gain most from the implementation of MV-based Q4.0. Through analysis and synthesis of the literature, the study reveals the lack of an integrated approach combining both MV-based Q4.0 and MFGRES. This is particularly clear during disruptions.

Research limitations/implications:
This study addresses only the Scopus database. Furthermore, further empirical study on the subject needs to be added to this study. Within the same research domain, it would be interesting to evaluate the effect of MV-based Q4.0 on MFGRES. Instead of concentrating solely on the Scopus database as in this paper, researchers may also need to investigate the various databases more broadly while using different keywords.

Practical implications:
This study has a significant impact on managers and businesses. It also advances knowledge of the importance of MV-based Q4.0 in achieving MFGRES and gaining its full rewards.

This paper makes significant recommendations for academics, particularly those who are interested in the metaverse concept within MFGRES. The study also helps managers by illuminating a key area to concentrate on for the improvement of MFGRES within their organizations. In light of this, future research directions are suggested.

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