Fuzzy-FMEA risk evaluation approach for LHD machine-A case study

Jakkula, Balaraju; Raj, M. Govinda; Murthy, C. S.

doi:10.1016/j.jsm.2019.08.002

Cited by 81 publications

(48 citation statements)

References 18 publications

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“…It is also possible to combine fuzzy logic with other decision-making methods. Fuzzy logic has been used to analyze occupational health and safety [9][10][11], for risk assessments of various equipment failures [12], for a pipeline risk assessment [13], for a deepwater drilling riser [14], and in mining equipment [15]. It has also been used in Risk Based Maintenance (RBM) [16][17][18].…”

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confidence: 99%

Fuzzy Model for Risk Assessment of Machinery Failures

et al. 2020

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The main goal of this research was the development of an algorithm for the implementation of negative risk parameters in a synthesis model for a risk level assessment for a specific machine used in the mining industry. Fuzzy sets and fuzzy logic theory, in combination with statistical methods, were applied to analyze the time picture state of the observed machine. Fuzzy logic is presented through fuzzy proposition and a fuzzy composition module. Using these tools, the symmetric position of the fuzzy sets with regard to class was used, and the symmetric fuzzy inference approach was used in an outcome calculation. The main benefit of the proposed model is being able to use numerical and linguistic data in a risk assessment model. The proposed risk assessment model, using fuzzy logic conclusions and min–max composition, was used on a mobile crushing machine. The results indicated that the risk level of the mobile crushing machine was in the “high” category, which means that it is necessary to introduce maintenance policies based on this high risk. The proposed risk assessment model is useful for any engineering system.

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confidence: 99%

Fuzzy Model for Risk Assessment of Machinery Failures

et al. 2020

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“…Pun et al [32] applied Fuzzy Integrated FMEA to the NPD process in the flexible electronics field. The literature additionally includes combinations using FMEA and Fuzzy techniques [19,[33][34][35][36][37]. Later, Khalilzadeh et al [38] applied the Best Worst Method and GRA-VIKOR mixed with fuzzy logic methods for oil and gas projects; the authors concluded that the prioritization of risks is better compared to the conventional FMEA method.…”

Section: Failure Mode and Effect Analysis (Fmea) Literature Reviewmentioning

confidence: 99%

PFDA-FMEA, an Integrated Method Improving FMEA Assessment in Product Design

et al. 2021

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Product Design (PD) currently faces challenges in new product development, since the industry is in a rush to introduce new products into the market, with customers demanding products that are faster, cheaper, and free from failure. In addition, global companies are trying to improve their product design risk assessment process to gain advantages over competitors, using proven tools like Failure Mode and Effect Analysis (FMEA) and mixing risk assessment methods. However, with current risks assessment tools and a combination of other methods, there is the opportunity to improve risk analysis. This document aims to reveal a novel integrated method, where FMEA, Pythagorean Fuzzy Sets (PFS), and Dimensional Analysis (DA) are cohesive in one model. The proposed method provides an effective technique to identify risks and remove uncertainty and vagueness of human intervention during risk assessment using the Failure Mode and Effect Analysis method. A real-life problem was carried out to illustrate the proposed method. Finally, the study was substantiated by using a correlation and sensitivity analysis, demonstrating the presented integrated method’s usefulness in decision-making and problem-solving.

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“…Secara umum, dapat diasumsikan bahwa semua parameter indeks risiko memiliki peran yang sama dalam penentuan prioritas. Nilai RPN pada Tabel 6 yang memiliki jumlah mode kegagalan yang sama di setiap komponennya maka dapat diperkirakan dengan persamaan berikut (Balaraju et al, 2019):…”

Section: Metodologiunclassified

Pendekatan FMEA dalam Analisa Risiko Perawatan Sistem Bahan Bakar Mesin Induk: Studi Kasus di KM. Sidomulyo

Yaqin

Zamri

Siahaan

et al. 2020

JRSI

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The fuel system is one of the main engine support systems which is very important in the operation of the KM Sidomulyo main engine. Main engine on ships are operated 24 hours a week or more. The operation main engine needs special treatment of the components on the main engine to prevent failure during operation. Failure Mode and Effect Analysis (FMEA) is a method that can be used to identify the priority scale in maintaining a machine by evaluating the risk of failure that occurs on the machine. This study applies FMEA to determine the priority scale for the maintenance of the KM Sidomulyo main engine fuel system. The results of the identification using FMEA, namely the injector and fuel filter components are components that must be prioritized for maintenance. The Risk Priority Number (RPN) values of the injector and fuel filter components are 192 and 168, respectively. Maintenance priority is based on the component RPN value is above the critical RPN value of the main engine fuel system and includes the priority component on the Pareto diagram. The type of maintenance applied to the injector component is checking dirty fuel which can cause the injector to operate less optimally. While the fuel filter component is cleaning the deposits on the fuel filter cartridge. It is recommended that the inspection of other components be carried out so that the condition of the main engine fuel system has good reliability.

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Fuzzy-FMEA risk evaluation approach for LHD machine-A case study

Cited by 81 publications

References 18 publications

Fuzzy Model for Risk Assessment of Machinery Failures

Fuzzy Model for Risk Assessment of Machinery Failures

PFDA-FMEA, an Integrated Method Improving FMEA Assessment in Product Design

Pendekatan FMEA dalam Analisa Risiko Perawatan Sistem Bahan Bakar Mesin Induk: Studi Kasus di KM. Sidomulyo

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