FRAM-AHP: A Resilience Engineering Approach for Sustainable Prevention

Rosa, Lucio Villarinho; Carvalho, Paulo Victor Rodrigues de; Haddad, Assed

doi:10.1007/978-3-030-41486-3_14

Cited by 5 publications

(1 citation statement)

References 22 publications

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“…Another limitation is related to the evaluation of the potential variability of functions, which in our case study was established in a qualitative manner during meetings with the group of experts. However, to overcome the ambiguity and reduce the subjectivity in the evaluation processes, tools capable of supporting decision makers to handle the complex interrelations of the functions and their variability can be used, such as the Analytic Hierarchy Process (AHP) method, which can guarantee a good balance between targets, understanding, and objectivity as suggested among others by Rosa et al [70] and Alboghobeish et al [71], or via detailed investigations of functional interactions [72]. Additionally, the use of mathematical simulation models can improve the quantification of variability in complex systems, reducing FRAM deficiencies [73].…”

Section: Discussionmentioning

confidence: 99%

A Resilience Engineering Approach for the Risk Assessment of IT Services

Fargnoli,

Murgianu

2023

Applied Sciences

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Nowadays, services related to IT technologies have assumed paramount importance in most sectors, creating complex systems involving different stakeholders. Such systems are subject to unpredictable risks that differ from what is usually expected and cannot be properly managed using traditional risk assessment approaches. Consequently, ensuring their reliability represents a critical task for companies, which need to adopt resilience engineering tools to reduce the occurrence of failures and malfunctions. With this goal in mind, the current study proposes a risk assessment procedure for cloud migration processes that integrates the application of the Functional Resonance Analysis Method (FRAM) with tools aimed at defining specific performance requirements for the suppliers of this service. In particular, the Critical-To-Quality (CTQ) method was used to define the quality drivers of the IT platform customers, while technical standards were applied to define requirements for a security management system, including aspects relevant to the supply chain. Such an approach was verified by means of its application to a real-life case study, which concerns the analysis of the risks inherent to the supply chain related to cloud migration. The results achieved can contribute to augmenting knowledge in the field of IT systems’ risk assessment, providing a base for further research.

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Section: Discussionmentioning

confidence: 99%

A Resilience Engineering Approach for the Risk Assessment of IT Services

Fargnoli,

Murgianu

2023

Applied Sciences

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Improving safety in complex systems: A review of integration of functional resonance analysis method with semi‐quantitative and quantitative approaches

Kumar,

Upadhyay,

Samanta

et al. 2024

Hum Ftrs & Erg Mfg Svc

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Functional resonance analysis method (FRAM) is extensively employed in analyzing and managing performance variabilities. Additionally, semi‐quantitative and quantitative methods have been increasingly integrated with the FRAM to analyze complex socio‐technical systems to improve safety levels. This review article presents a comprehensive and updated survey of current literature focused on semi‐quantitative and quantitative methods employed for quantifying performance variabilities and exploring aggregation/propagation rules. A total of 1659 studies published between 2012 and March 2024 from various scientific databases were systematically examined using preferred reporting items for systematic review and meta‐analysis, identifying 29 studies that met inclusion criteria. The identified studies were categorized into four groups based on the quantitative methods employed: Monte Carlo simulation, fuzzy logic, cognitive reliability and error analysis method, and miscellaneous approaches. While different methodologies had unique strengths, they commonly relied on expert judgment for data collection, whether for defining probability distributions in Monte Carlo simulations, membership functions, and fuzzy rule bases in fuzzy inference systems, or selecting common performance conditions, determining their interrelationships, and assigning scores. Addressing bias from expert judgment in assessing performance variabilities can be achieved by using suitable experts' opinions integration techniques, and leading safety indicators in the analysis.

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