Operationalizing Industry 5.0 in Automotive Manufacturing: Enabling Technologies, Human–Machine Collaboration, and Industrial Implementation

Industry 5.0 redirects digitally enabled manufacturing toward human-centricity, sustainability, and resilience. This structured integrative review examines its operationalization in automotive manufacturing using 137 eligible studies from two search streams. Searches were conducted between 20 and 28 September 2026. Article full-text assessment was recorded for 75 studies (54.7%); 62 were assessed from abstracts and bibliographic or publisher information. The analytical framework links technology, manufacturing application, human role, pillar relevance, reported outcome, and deployment maturity. The corpus contains 102 direct automotive studies, 30 transferable manufacturing studies, and five supporting studies. Human-centricity is more prominent in the recorded pillar coding than sustainability or resilience. This ordering also occurs in the 54 full-text-verified direct automotive studies, although coding prominence does not establish measured effectiveness. Representative cases show that plant-level deployment can coexist with limited evidence of worker, environmental, or recovery outcomes. The review proposes testable operationalization conditions and a staged implementation pathway. Its findings support separate reporting of deployment maturity, pillar relevance, and outcome substantiation. Stronger lifecycle measurement, disturbance-based resilience testing, and longitudinal worker assessment are needed.

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Publication Details

Journal
Machines
Published
2026-11-02
DOI
https://doi.org/10.3390/machines14111282
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
0.00

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Operationalizing Industry 5.0 in Automotive Manufacturing: Enabling Technologies, Human–Machine Collaboration, and Industrial Implementation

Patrik Šarga, Róbert Rákay, Tibor Krenický, Stella Hrehová
5 links
Machines
Digital Transformation in Industry
article

Operationalizing Industry 5.0 in Automotive Manufacturing: Enabling Technologies, Human–Machine Collaboration, and Industrial Implementation

Patrik Šarga, Róbert Rákay, Tibor Krenický, Stella Hrehová
article en

Abstract

Industry 5.0 redirects digitally enabled manufacturing toward human-centricity, sustainability, and resilience. This structured integrative review examines its operationalization in automotive manufacturing using 137 eligible studies from two search streams. Searches were conducted between 20 and 28 September 2026. Article full-text assessment was recorded for 75 studies (54.7%); 62 were assessed from abstracts and bibliographic or publisher information. The analytical framework links technology, manufacturing application, human role, pillar relevance, reported outcome, and deployment maturity. The corpus contains 102 direct automotive studies, 30 transferable manufacturing studies, and five supporting studies. Human-centricity is more prominent in the recorded pillar coding than sustainability or resilience. This ordering also occurs in the 54 full-text-verified direct automotive studies, although coding prominence does not establish measured effectiveness. Representative cases show that plant-level deployment can coexist with limited evidence of worker, environmental, or recovery outcomes. The review proposes testable operationalization conditions and a staged implementation pathway. Its findings support separate reporting of deployment maturity, pillar relevance, and outcome substantiation. Stronger lifecycle measurement, disturbance-based resilience testing, and longitudinal worker assessment are needed.

MachinesVol. 14(11)
Technical University of Košice (SK)
European Commission
Industry, innovation and infrastructure
Openalex Percentile: Top 16%
Digital Transformation in Industry
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Operationalizing Industry 5.0 in Automotive Manufacturing: Enabling Technologies, Human–Machine Collaboration, and Industrial Implementation — Patrik Šarga, Róbert Rákay, et al. · Machines (2026) | TGRS Research Map | TGRS