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This is a Quantitative Study study.

October 1, 2025Facta Universitatis Series Mechanical EngineeringOpen Access

A Modified Fmea Approach Based Integrated Decision Framework for Overcoming the Problems of Sudden Failure and Accidental Hazards in Turbine and Alternator Unit

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Authors

DKDinesh Kumar KushwahaGS Engineering (United States)DPDilbagh PanchalNational Institute of Technology Kurukshetra ASAnish SachdevaDr. B. R. Ambedkar National Institute of Technology Jalandhar

Discussion

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Overview

This framework employs intuitionistic fuzzy methodologies to evaluate risk factors in turbine systems, highlighting critical failure causes and maintenance plans.

Key Points

The proposed integrated decision framework improves risk assessment for turbine and alternator units in industries.
Key factors include probability of occurrence, severity, and detection, which influence failure analysis outcomes.
Sensitivity analysis affirms the robustness of the intuitionistic fuzzy model in addressing operational issues.
Findings enable better maintenance planning in chemical process industries globally, ultimately minimizing sudden breakdowns.

Cite This Study

Kushwaha et al. (2023) studied this question.

synapsesocial.com/papers/68dd953bfe798ba2fc499d47 https://doi.org/10.22190/fume221126010k

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October 1, 2025Facta Universitatis Series Mechanical EngineeringOpen Access

A Modified Fmea Approach Based Integrated Decision Framework for Overcoming the Problems of Sudden Failure and Accidental Hazards in Turbine and Alternator Unit

View Full Paper

Ask AI

Bookmark

Authors

DKDinesh Kumar KushwahaGS Engineering (United States)DPDilbagh PanchalNational Institute of Technology Kurukshetra ASAnish SachdevaDr. B. R. Ambedkar National Institute of Technology Jalandhar

Discussion

Member takes

Overview

This framework employs intuitionistic fuzzy methodologies to evaluate risk factors in turbine systems, highlighting critical failure causes and maintenance plans.

Key Points

The proposed integrated decision framework improves risk assessment for turbine and alternator units in industries.
Key factors include probability of occurrence, severity, and detection, which influence failure analysis outcomes.
Sensitivity analysis affirms the robustness of the intuitionistic fuzzy model in addressing operational issues.
Findings enable better maintenance planning in chemical process industries globally, ultimately minimizing sudden breakdowns.

Cite This Study

Kushwaha et al. (2023) studied this question.

synapsesocial.com/papers/68dd953bfe798ba2fc499d47 https://doi.org/10.22190/fume221126010k

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