1,478 research outputs found
Application Of Intuitionistic Fuzzy Topsis Model For Troubleshooting An Offshore Patrol Boat Engine
In this paper, an Intuitionistic Fuzzy TOPSIS model which is based on a score function is proposed for detecting the root cause of failure in an Offshore Boat engine, using groups of expert’s opinions. The study which has provided an alternative approach for failure mode identification and analysis in machines, addresses the machine component interaction failures which is a limitation in existing methods. The results from the study show that although early detection of failures in engines is quite difficult to identify due to the dependency of their systems from each other. However, with the Intuitionistic Fuzzy TOPSIS model which is based on an improved score function such faults/failures are easily detected using expert’s based opinions
Integrated Frameworks for Effective Multi-criteria Decision Making in Reliability Centred Maintenance of Industrial Machines
No abstract availabl
Multi criteria risk analysis of a subsea BOP system
The Subsea blowout preventer (BOP) which is latched to a subsea wellhead is
one of several barriers in the well to prevent kicks and blowouts and it is the
most important and critical equipment, as it becomes the last line of protection
against blowout. The BOP system used in Subsea drilling operations is
considered a Safety – Critical System, with a high severity consequence
following its failure. Following past offshore blowout incidents such as the most
recent Macondo in the Gulf of Mexico, there have been investigations, research,
and improvements sought for improved understanding of the BOP system and
its operation. This informs the need for a systematic re-evaluation of the Subsea
BOP system to understand its associated risk and reliability and identify critical
areas/aspects/components.
Different risk analysis techniques were surveyed and the Failure modes effect
and criticality analysis (FMECA) selected to be used to drive the study in this
thesis. This is due to it being a simple proven cost effective process that can
add value to the understanding of the behaviours and properties of a system,
component, software, function or other. The output of the FMECA can be used
to inform or support other key engineering tasks such as redesigning, enhanced
qualification and testing activity or maintenance for greater inherent reliability
and reduced risk potential. This thesis underscores the application of the
FMECA technique to critique associated risk of the Subsea BOP system.
System Functional diagrams was developed with boundaries defined, a FMECA
were carried out and an initial select list of critical component failure modes
identified. The limitations surrounding the confidence of the FMECA failure
modes ranking outcome based on Risk priority number (RPN) is presented and
potential variations in risk interpretation are discussed.
The main contribution in this thesis is an innovative framework utilising
Multicriteria decision making (MCDA) analysis techniques with consideration of
fuzzy interval data is applied to the Subsea BOP system critical failure modes
from the FMECA analysis. It utilised nine criticality assessment criteria deduced
from expert consultation to obtain a more reliable ranking of failure modes. The MCDA techniques applied includes the technique for order of Preference for
similarity to the Ideal Solution (TOPSIS), Fuzzy TOPSIS, TOPSIS with interval
data, and Preference Ranking Organization Method for Enrichment of
Evaluations (PROMETHEE). The outcome of the Multi-criteria analysis of the
BOP system clearly shows failures of the Wellhead connector, LMRP hydraulic
connector and Control system related failure as the Top 3 most critical failure
with respect to a well control. The critical failure mode and components
outcome from the analysis in this thesis is validated using failure data from
industry database and a sensitivity analysis carried out. The importance of
maintenance, testing and redundancy to the BOP system criticality was
established by the sensitivity analysis. The potential for MCDA to be used for
more specific analysis of criteria for a technology was demonstrated.
Improper maintenance, inspection, testing (functional and pressure) are critical
to the BOP system performance and sustenance of a high reliability level.
Material selection and performance of components (seals, flanges, packers,
bolts, mechanical body housings) relative to use environment and operational
conditions is fundamental to avoiding failure mechanisms occurrence. Also
worthy of notice is the contribution of personnel and organisations (by way of
procedures to robustness and verification structure to ensure standard expected
practices/rules are followed) to failures as seen in the root cause discussion.
OEMs, operators and drilling contractors to periodically review operation
scenarios relative to BOP system product design through the use of a Failure
reporting analysis and corrective action system. This can improve design of
monitoring systems, informs requirement for re-qualification of technology
and/or next generation designs. Operations personnel are to correctly log in
failures in these systems, and responsible Authority to ensure root cause
analysis is done to uncover underlying issue initiating and driving failures
A Review of Failure Mode and Effects Analysis (FMEA) for Sustainable Manufacturing and Improvement in Electrostatic Chuck Manufacture and Operation
Failure modes and effect analysis (FMEA) is widely used in industry to quantify, mitigate, and eliminate risk for products and processes. It has the potential to be an important technique in supporting sustainable manufacturing by reducing the risks associated with transitioning to more sustainable processes. Whilst traditional FMEA does quantify risk by calculating a risk priority number (RPN), there are limitations to the usefulness of this due to the lack of objectiveness inherent in the method. In this paper improvements to the traditional FMEA approach are reviewed and their appropriateness in the specific case of the manufacture of electrostatic chucks (ESC) is considered.</p
A STRUCTURED FRAMEWORK FOR RELIABILITY AND RISK EVALUATION IN THE MILK PROCESS INDUSTRY UNDER FUZZY ENVIRONMENT
This paper aims at proposing a novel integrated framework for studying reliability and risk issues of the curd unit in a milk process industry under uncertain environment. The considered plant’s complex series-parallel configuration was presented using the Petri Net (PN) modeling. The Fuzzy Lambda-Tau (λ-τ) approach was applied to study and analyze the reliability aspects of the considered plant. Failure dynamics of the curd unit has been analyzed with respect to increasing/ decreasing trends of the tabulated reliability indices. Availability of the considered plant shows a decreasing trend with an increase in spread values. For improving the system’s availability, a risk analysis was done to identify the most critical failure causes. Using the traditional FMEA approach, the FMEA sheet was generated on the basis of expert’s knowledge/experience. The Fuzzy-Complex Proportional Assessment (FCOPRAS) approach was applied within FMEA approach for identification of critical failure causes associated with different subsystem/components of the considered plant. In order to check the consistency of the ranking results, the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) was applied within the FCOPRAS approach. Ranking results are compared for checking consistency and robustness of critical failure causes related decision making which would be useful in designing the finest maintenance schedule for the considered curd unit. Overheating/moisture lead to winding failure (MSCP5), visible sediment of milk jam in filter (MBFP3), improper quality of oil (H4), blade breakage (CTK4), wearing in gears (PFM11), and cylinder leakage (CFM7) were recognized as the most critical failure causes contributing to system unavailability. The analysis results were supplied to the maintenance manager for framing a suitable time-based maintenance intervals policy for the considered unit
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