Reliability Modelling and Safety Learning Algorithms in Complex Risk Multifunctional Systems

Kingsley E. Abhulimen

Reliability Modelling and Safety Learning Algorithms in Complex Risk Multifunctional Systems

Kingsley E. Abhulimen * §

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syntexacad §

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§ Department of Chemical Engineering

Reliability Modelling and Safety Learning Algorithms in Complex Risk Multifunctional Systems

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SFR74887

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Abstract

Modelling safety procedures of complex risk systems of multifunctional production systems such as floating production storage and offloading (FPSO) vessels is typically rigorous. Deterministic modelling and Learning algorithms are normally used to generate whole sets of hazard data based on data of intrinsic risk events and safety measures incorporated. The model developed use failure data systems obtained from operator of multifunctional production systems of FPSO to generate fuzzy class surrogates based on learning algorithms to rank safety index. Thus classifications of risk events in a fuzzy set of system is predicted used weighted like hood of failure of human, process, mechanical, electrical, operational, in composite risk system to set the safety thresholds. The model used a learning constraint function in probable risk outcomes to match retroactively weights index of actual scenarios in skewed hazard surrogates to specific risk and safety ratings criteria. The MTBR (Mean Time before Repair) to plan maintainability studies and safety programmes were simulated to an optimal repair range from almost 0.5 yrs for worst case; fuzzy class 1 with safety rating of 0.0 to almost 5 million years for best case when the fuzzy class 5 with safety index rating of 1.0 assume availability is 80%.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Kingsley E. Abhulimen, syntexacad. 2020. "Reliability Modelling and Safety Learning Algorithms in Complex Risk Multifunctional Systems". Global Journal of Science Frontier Research - A: Physics & Space Science GJSFR-A Volume 20 (GJSFR Volume 20 Issue A3).

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GJSFR Volume 20 Issue A3

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Journal Specifications

Crossref Journal DOI 10.17406/GJSFR

Print ISSN 0975-5896

e-ISSN 2249-4626

Keywords

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Classification

GJSFR-A Classification FOR Code: 280401

Submission ReceivedOctober 2, 2019
Peer Review Double Blind
Handling Editor
Accepted October 25, 2019
Published April 8, 2020

Version of record

v1.2

Issue date

April 8, 2020

Language

English

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Article Matrices

Total Score: 101

Country: Nigeria

Subject: Global Journal of Science Frontier Research - A: Physics & Space Science

Authors: Kingsley E. Abhulimen (PhD/Dr. count: 0)

View Count (all-time): 289

Total Views (Real + Logic): 902

Total Downloads (simulated): 67

Publish Date: 2019 11, Mon

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Total Views: 902

Total Downloads: 67

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