Document Type

Article

Publication Date

2021

DOI

10.1016/j.procs.2021.01.350

Publication Title

Procedia Computer Science

Volume

180

Pages

1049–1058

Abstract

Over the last few years, the Human Factors and Ergonomics (HF/E) discipline has significantly benefited from new human-centric engineered digital solutions of the 4.0 industrial age. Technologies are creating new socio-technical interactions between human and machine that minimize the risk of design-induced human errors and have largely contributed to remarkable improvements in terms of process safety, productivity, quality, and workers’ well-being. However, despite the Oil&Gas (O&G) sector is one of the most hazardous environments where human error can have severe consequences, Industry 4.0 aspects are still scarcely integrated with HF/E. This paper calls for a holistic understanding of the changing role and responsibilities of workers in the O&G industry and aims at investigating to what extent, what type of, and how academic publications in the O&G field integrate HF/E and Industry 4.0 in their research. Bibliometric analysis has been conducted to provide useful insights to researchers and practitioners and to assess the status quo. Our findings show that academic publications have mainly focused on simulation-based training to increase process safety whereas revealed the lack of specific studies on the application of cognitive solutions, such as Augmented Reality-enabled tools or Intelligent Fault Detection and Alarm Management solutions.

Rights

© 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the International Conference on Industry 4.0 and Smart Manufacturing

Original Publication Citation

Longo, F., Padovano, A., Gazzaneo, L., Frangella, J., & Diaz, R. (2021). Human factors, ergonomics and Industry 4.0 in the Oil & Gas industry: A bibliometric analysis. Procedia Computer Science, 180, 1049-1058. https://doi.org/10.1016/j.procs.2021.01.350

ORCID

0000-0002-8637-5967 (Diaz)

Download

Share

COinS