Risk Identification of FPSO Oil and Gas Processing System Based on an Improved FMEA Approach

2021 ◽  
Vol 11 (2) ◽  
pp. 567
Author(s):  
Longting Wang ◽  
Liping Sun ◽  
Jichuan Kang ◽  
Yanfu Wang ◽  
Haiqing Wang
Keyword(s):  
Subjective Experience ◽  
Failure Modes ◽  
Oil And Gas ◽  
Relative Weight ◽  
Processing System ◽  
Fuzzy Topsis ◽  
Risk Identification ◽  
Effect Analysis ◽  
Solution Approach ◽  
Gas Processing

It is increasingly necessary to perform risk analysis in marine structures, to ensure system safety, as they are large and complex. In view of the shortcomings of failure mode and effect analysis (FMEA), a modified fuzzy TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) approach is proposed that is based on fuzzy evidence reasoning (FER), and considers the risk factor rating and relative weight. The presented method is used to prioritize the risk of equipment failure modes for the floating production storage and offloading system (FPSO) oil and gas processing system. The subjective weights and objective weights of occurrence (O), severity (S), and detectability (D) have been considered comprehensively. The subjective experience of the experts and the objective information reflected by the O, S, and D ratings are all included in the weights, making the ranking results closer to reality. The results can be scientific references for decision-makers in risk identification.

Reliability Analysis of FPSO Oil and Gas Processing System Based on Petri Net

2020 ◽  
Author(s):  
Jichuan Kang ◽  
Xinyuan Geng ◽  
Liping Sun ◽  
Peng Jin
Keyword(s):  
Petri Net ◽  
Evaluation Method ◽  
Failure Modes ◽  
Oil And Gas ◽  
Solution Process ◽  
Processing System ◽  
Fuzzy Synthetic Evaluation ◽  
Weather Factors ◽  
Reliability Data ◽  
Gas Processing

Abstract This paper aims to introduce a novel method in terms of risk analysis and control of FPSO oil and gas processing system. The Failure Mode and Effect Analysis (FMEA) is implemented to identify the critical equipment and typical failure modes, in order to improve the accuracy and pertinence of model establishment. A Petri Net model is then developed based on FMEA results and the correlation analysis between different components. The input reliability data are primarily collected from Offshore and Onshore Reliability Data (OREDA), and the maintenance information is assessed by industry experts, using fuzzy synthetic evaluation method. This paper focuses on the accuracy, rapidity and feasibility in the modeling and solution process, and considers the influence of weather factors on the maintenance operation and limited maintenance crew number, forming a complete set of reliability and maintenance strategy optimization analysis method of FPSO oil and gas processing system. The results contain system reliability, availability, and maintenance information. The proposed approach can reveal the risk feature of the system and provide corresponding risk control scheme.

Reliability Analysis of Fpso Oil and Gas Processing System Based on Petri Net

2021 ◽  
Author(s):  
Jichuan Kang ◽  
Liping Sun ◽  
Xinyuan Geng ◽  
Peng Jin
Keyword(s):  
Reliability Analysis ◽  
Petri Net ◽  
Oil And Gas ◽  
Processing System ◽  
Gas Processing

scholarly journals Identification and Prioritization of Risk Factors in an Electrical Generator Based on the Hybrid FMEA Framework

Energies ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 649 ◽  
Author(s):  
Moath Alrifaey ◽  
Tang Sai Hong ◽  
Eris Supeni ◽  
Azizan As’arry ◽  
Chun Ang
Keyword(s):  
Failure Modes ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Analytic Network Process ◽  
Gas Industry ◽  
Effect Analysis ◽  
Gas Leakage ◽  
Network Process ◽  
Electrical Generator ◽  
Hybrid Distribution

The oil and gas industry is looking for ways to accurately identify and prioritize the failure modes (FMs) of the equipment. Failure mode and effect analysis (FMEA) is the most important tool used in the maintenance approach for the prevention of malfunctioning of the equipment. Current developments in the FMEA technique are mainly focused on addressing the drawbacks of the conventional risk priority number calculations, but the group effects and interrelationships of FMs on other measurements are neglected. In the present study, a hybrid distribution risk assessment framework was proposed to fill these gaps based on the combination of modified linguistic FMEA (LFMEA), Analytic Network Process (ANP), and Decision Making Trial and Evaluation Laboratory (DEMATEL) techniques. The hybrid framework of FMEA was conducted in a hazardous environment at a power generation unit in an oil and gas plant located in Yemen. The results show that mechanical and gas leakage FM in electrical generators posed a greater risk, which critically affects other FMs within the plant. It was observed that the suggested framework produced a precise ranking of FMs, with a clear relationship among FMs. Also, the comparisons of the proposed framework with previous studies demonstrated the multidisciplinary applications of the present framework.

Risk identification of a hospital laboratory pre-analytics through failure mode and effect analysis

2021 ◽  
Vol 12 (4) ◽  
pp. 31-38
Author(s):  
Debdatta Das ◽  
Krishna Pal ◽  
Sudip Roy ◽  
Moushumi Lodh
Keyword(s):  
Patient Safety ◽  
Failure Mode ◽  
Laboratory Testing ◽  
Failure Modes ◽  
Risk Identification ◽  
Post Intervention ◽  
Effect Analysis ◽  
Laboratory Errors ◽  
Corrective Actions ◽  
Analytical Phase

Background: Implementing an active system to identify, monitor and manage risk from laboratory errors can enhance patient safety and quality of care. Aims and Objectives: Failure Mode and Effect Analysis (FMEA) technique allows evaluating and measuring the hazards of a process malfunction, to decide where to execute improvement actions, and to measure the outcome of those actions. The aim of this study was to assess pre analytical phase of laboratory testing, mitigate risk and thereby increase patient safety. Materials and Methods: Steps followed in the study were: planning the study, selecting team members, analysis of the processes, risk analysis, and developing a risk reduction protocol by incorporating corrective actions. A Fault Tree Analysis diagram was used to plot the cascade of faults leading to the pre analytical errors. Risk Priority Number (RPN) was assigned. A minimum cut- off 40 RPN was considered for interventions and highest RPN errors were prioritized with corrective actions. Post intervention RPN score was calculated. Results: Eight failure modes had the highest RPN. Corrective actions were prioritized against these errors. RPN scores of test ordering error, sample collection error, transport errors, error in patient identification, site selection, urine samples not received, sample accessioning and sample processing errors decreased, post intervention. Conclusion: With thorough planning, we can use FMEA as a common standard to analyze risk in pre analytical phase of laboratory testing.

Failure mode and effect analysis (FMEA) to improve collaborative project-based learning: Case study of a Study and Research Path in mechanical engineering

2021 ◽  
pp. 030641902199904
Author(s):  
Elena Bartolomé ◽  
Paula Benítez
Keyword(s):  
Active Learning ◽  
Failure Mode ◽  
Mechanical Engineering ◽  
Failure Modes ◽  
Collaborative Study ◽  
Project Based Learning ◽  
Educational Process ◽  
Effect Analysis ◽  
Questions And Answers

Failure Mode and Effect Analysis (FMEA) is a powerful quality tool, widely used in industry, for the identification of failure modes, their effects and causes. In this work, we investigated the utility of FMEA in the education field to improve active learning processes. In our case study, the FMEA principles were adapted to assess the risk of failures in a Mechanical Engineering course on “Theory of Machines and Mechanisms” conducted through a project-based, collaborative “Study and Research Path (SRP)” methodology. The SRP is an active learning instruction format which is initiated by a generating question that leads to a sequence of derived questions and answers, and combines moments of study and inquiry. By applying the FMEA, the teaching team was able to identify the most critical failures of the process, and implement corrective actions to improve the SRP in the subsequent year. Thus, our work shows that FMEA represents a simple tool of risk assesment which can serve to identify criticality in educational process, and improve the quality of active learning.

Fuzzy risk assessment for electro-optical target tracker

2016 ◽  
Vol 33 (6) ◽  
pp. 830-851 ◽  
Author(s):  
Soumen Kumar Roy ◽  
A K Sarkar ◽  
Biswajit Mahanty
Keyword(s):  
Failure Mode ◽  
Failure Modes ◽  
Linear Equations ◽  
Mode Analysis ◽  
Failure Behavior ◽  
Membership Functions ◽  
Design And Development ◽  
Effect Analysis ◽  
Content Type ◽  
Criticality Analysis

Purpose – The purpose of this paper is to evolve a guideline for scientists and development engineers to the failure behavior of electro-optical target tracker system (EOTTS) using fuzzy methodology leading to success of short-range homing guided missile (SRHGM) in which this critical subsystems is exploited. Design/methodology/approach – Technology index (TI) and fuzzy failure mode effect analysis (FMEA) are used to build an integrated framework to facilitate the system technology assessment and failure modes. Failure mode analysis is carried out for the system using data gathered from technical experts involved in design and realization of the EOTTS. In order to circumvent the limitations of the traditional failure mode effects and criticality analysis (FMECA), fuzzy FMCEA is adopted for the prioritization of the risks. FMEA parameters – severity, occurrence and detection are fuzzifed with suitable membership functions. These membership functions are used to define failure modes. Open source linear programming solver is used to solve linear equations. Findings – It is found that EOTTS has the highest TI among the major technologies used in the SRHGM. Fuzzy risk priority numbers (FRPN) for all important failure modes of the EOTTS are calculated and the failure modes are ranked to arrive at important monitoring points during design and development of the weapon system. Originality/value – This paper integrates the use of TI, fuzzy logic and experts’ database with FMEA toward assisting the scientists and engineers while conducting failure mode and effect analysis to prioritize failures toward taking corrective measure during the design and development of EOTTS.

The calculation of required fire resistance limits for engineering structures of technological pipe racks at oil and gas processing plants on the basis of an evaluation of the time needed for personnel evacuation and rescue in case of fire

2021 ◽  
Vol 30 (5) ◽  
pp. 58-65
Author(s):  
A. Yu. Shebeko ◽  
Yu. N. Shebeko ◽  
A. V. Zuban
Keyword(s):  
Fire Resistance ◽  
Oil And Gas ◽  
Probabilistic Method ◽  
Processing Plant ◽  
Engineering Structures ◽  
Gas Processing ◽  
Processing Plants ◽  
The One ◽  
In Fire ◽  
Rescue Time

Introduction. GOST R 12.3.047-2012 standard offers a methodology for determination of required fire resistance limits of engineering structures. This methodology is based on a comparison of values of the fire resistance limit and the equivalent fire duration. However, in practice incidents occur when, in absence of regulatory fire resistance requirements, a facility owner, who has relaxed the fire resistance requirements prescribed by GOST R 12.3.047–2012, is ready to accept its potential loss in fire for economic reasons. In this case, one can apply the probability of safe evacuation and rescue to compare distributions of fire resistance limits, on the one hand, and evacuation and rescue time, on the other hand.A methodology for the identification of required fire resistance limits. The probabilistic method for the identification of required fire resistance limits, published in work [1], was tested in this study. This method differs from the one specified in GOST R 12.3.047-2012. The method is based on a comparison of distributions of such random values, as the estimated time of evacuation or rescue in case of fire at a production facility and fire resistance limits for engineering structures.Calculations of required fire resistance limits. This article presents a case of application of the proposed method to the rescue of people using the results of full-scale experiments, involving a real pipe rack at a gas processing plant [2].Conclusions. The required fire resistance limits for pipe rack structures of a gas processing plant were identified. The calculations took account of the time needed to evacuate and rescue the personnel, as well as the pre-set reliability of structures, given that the personnel evacuation and rescue time in case of fire is identified in an experiment.

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