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Cited by 649

The DOI matches its Crossref record; 86 of the 86 references it cites were found in a registry or an index.

Methods and models in process safety and risk management: Past, present and future

Open access
Khan, Faisal, Rathnayaka, Samith, Ahmed, Salim·2015·Process Safety and Environmental Protection

Abstract

The paper reviews past progress in the development of methods and models for process safety and risk management and highlights the present research trends; also it outlines the opinions of the authors regarding the future research direction in the field. Based on the open literature published in the leading journals in the field of safety, risk and reliability, the review covers the evolution of the methods and models developed for process safety and risk management. The methods and models are categorized as qualitative, semi-quantitative, quantitative and hybrid. The progress in the last few decades is discussed in the context of the past. Developments in the current decade formulate the basis of the present trends; future directions for research in these fields are also outlined. The aim of the article is to provide a historical development in this field with respect to the driving forces behind the development. It is expected that it will help researchers and industrial practitioners to gain a better understanding of the existing concepts. At the same time the aim is to provide direction to bridge the existing gaps through research and developments.

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Crossref · 10.1016/j.psep.2015.07.005

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Metadata

Authors
Khan, F., Rathnayaka, S., & Ahmed, S.
Venue
Process Safety and Environmental Protection
Publisher
Elsevier BV
Published
2015-11
Volume
98
Pages
116-147
ISSN
  • 0263-8762 (ISSN-L)
  • 0957-5820
OpenAlex
W1837982956
Cited by
649
References
86
FWCI
25.12
Type
journal article
Language
en
Open access
green

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Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.