Application of complex spherical fuzzy failure mode, effects, and criticality analysis for assessing potential risk of Maritime Autonomous Surface Ships (MASS)

Abstract Due to increased system complexity, cyber interdependencies, and decreased human oversight, Maritime Autonomous Surface Ships (MASS) present new operational perspective that pose a challenge to traditional risk analysing techniques. The aim of this article is to apply complex spherical fuzzy failure mode effects and criticality analysis for potential risks associated with MASS (degree-3) operations. The proposed approach incorporates complex spherical fuzzy sets into traditional failure mode, effects, and critical analysis (FMECA) to address uncertainty and interrelated failure behaviours in multi-domain autonomous systems in maritime. Expert assessments were synthesized utilizing complex spherical fuzzy aggregation operators to assess severity, occurrence, and detectability of potential failure modes amid significant uncertainty. The risk priority number (RPN) offers an accurate and discerning classification of significant failure modes in comparison to traditional FMECA and conventional fuzzy extensions. The findings of the research show that FM9 (Human–machine interface-HMI) has the highest RPN and representing the most critical failure mode. The outputs of the article will provide utmost practical contributions to safety inspectors, superintendents, HSEQ managers, MASS operators and ship owners about potential MASS operational failure modes and RPN for safer and environmental operations.

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Publication Details

Journal
Discover Applied Sciences
Published
2026-07-01
DOI
https://doi.org/10.1007/s42452-026-09001-5
Primary Topic
Maritime Navigation and Safety
Type
article
Field-Weighted Citation Impact
0.00
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article

Application of complex spherical fuzzy failure mode, effects, and criticality analysis for assessing potential risk of Maritime Autonomous Surface Ships (MASS)

Agus Hasan, Emre Akyuz, Selcuk Cebi
Discover Applied Sciences
Maritime Navigation and Safety
article

Application of complex spherical fuzzy failure mode, effects, and criticality analysis for assessing potential risk of Maritime Autonomous Surface Ships (MASS)

Agus Hasan, Emre Akyuz, Selcuk Cebi
article en

Abstract

Abstract Due to increased system complexity, cyber interdependencies, and decreased human oversight, Maritime Autonomous Surface Ships (MASS) present new operational perspective that pose a challenge to traditional risk analysing techniques. The aim of this article is to apply complex spherical fuzzy failure mode effects and criticality analysis for potential risks associated with MASS (degree-3) operations. The proposed approach incorporates complex spherical fuzzy sets into traditional failure mode, effects, and critical analysis (FMECA) to address uncertainty and interrelated failure behaviours in multi-domain autonomous systems in maritime. Expert assessments were synthesized utilizing complex spherical fuzzy aggregation operators to assess severity, occurrence, and detectability of potential failure modes amid significant uncertainty. The risk priority number (RPN) offers an accurate and discerning classification of significant failure modes in comparison to traditional FMECA and conventional fuzzy extensions. The findings of the research show that FM9 (Human–machine interface-HMI) has the highest RPN and representing the most critical failure mode. The outputs of the article will provide utmost practical contributions to safety inspectors, superintendents, HSEQ managers, MASS operators and ship owners about potential MASS operational failure modes and RPN for safer and environmental operations.

Discover Applied Sciences
Yıldız Technical University (TR), Azerbaijan State University of Economics (AZ), Istanbul Technical University (TR), Norwegian University of Life Sciences (NO)
Life below water
Openalex Percentile: Top 9%
Maritime Navigation and Safety
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Application of complex spherical fuzzy failure mode, effects, and criticality analysis for assessing potential risk of Maritime Autonomous Surface Ships (MASS) — Agus Hasan, Emre Akyuz, et al. · Discover Applied Sciences (2026) | TGRS Research Map | TGRS