A novel FMEA approach based on probabilistic linguistic best-worst method and TOPSIS with application to marine diesel fuel injection system

托普西斯 失效模式及影响分析 柴油 概率逻辑 计算机科学 可靠性工程 风险分析(工程) 柴油机 运筹学 汽车工程 工程类 人工智能 业务
作者
Qingguo Shi,Yihuai Hu,Guohua Yan
出处
期刊:Journal of Intelligent and Fuzzy Systems [IOS Press]
卷期号:45 (3): 3835-3854 被引量:3
标识
DOI:10.3233/jifs-230870
摘要

The failure mode and effect analysis (FMEA) is an effective tool to analyze risks and potential effects of complex systems, and it is one of the most widely used risk analysis methods for complex systems as there often exists various factors that could affect the operation of the complex systems. Conventional FMEA methods have been limited to using crisp values to represent the assessments, which has been criticized for having many deficiencies. Marine diesel fuel injection system is an important part of marine diesel engine, and its failure could directly affect the performance of the marine diesel engine and even impact the safe operation of the ship. However, little attention has been paid to the FMEA of the marine diesel fuel injection system. To this end, this paper presents a novel FMEA method based on the best-worst method (BWM) and TOPSIS method with probabilistic linguistic term set (PLTS). Firstly, the PLTS is used to represent the uncertain and linguistic judgments of experts. Then, the BWM is extended with PLTS to determine the weights of different elements for FMEA, and the TOPSIS is extended with PLTS to assess and rank different failure modes. Finally, a case study on marine diesel fuel injection is presented, and the most critical failures are identified for improvement measures. The results show that the proposed method could help managers and engineerings identify the most important failure modes for marine diesel fuel injection system.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
whatever应助飘逸山兰采纳,获得10
1秒前
meng发布了新的文献求助10
1秒前
1秒前
沉默寄凡发布了新的文献求助10
1秒前
刘豆发布了新的文献求助20
2秒前
苏遇安完成签到,获得积分10
2秒前
qu蛐完成签到 ,获得积分10
2秒前
zwyoo发布了新的文献求助10
2秒前
稞小弟完成签到,获得积分10
3秒前
minnie发布了新的文献求助10
4秒前
领导范儿应助秋秋采纳,获得10
4秒前
洽洽瓜子shine完成签到,获得积分10
4秒前
5秒前
情怀应助Corundum采纳,获得10
5秒前
诚心的访蕊完成签到 ,获得积分10
5秒前
5秒前
我是老大应助铎子采纳,获得10
5秒前
科研通AI6.1应助Jennie采纳,获得10
5秒前
阳光桐完成签到,获得积分10
5秒前
倒霉兔子完成签到,获得积分0
5秒前
科研通AI2S应助空巢小黄人采纳,获得10
6秒前
Brad_AN完成签到,获得积分10
7秒前
8秒前
奔跑的小熊仔应助Hh采纳,获得30
8秒前
slin_sjtu完成签到,获得积分0
8秒前
找论文机器完成签到,获得积分10
9秒前
阳光路灯完成签到,获得积分10
9秒前
9秒前
meng完成签到,获得积分10
9秒前
xq2277完成签到,获得积分10
9秒前
damnxas完成签到,获得积分10
9秒前
zhiren完成签到,获得积分10
9秒前
刘佳宇完成签到,获得积分10
10秒前
Vivid完成签到,获得积分10
10秒前
10秒前
susu完成签到 ,获得积分10
10秒前
殿祥G完成签到,获得积分10
10秒前
无极微光应助甜甜的盼海采纳,获得20
11秒前
11秒前
Linky完成签到 ,获得积分10
11秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Kinesiophobia : a new view of chronic pain behavior 3000
Les Mantodea de guyane 2500
Molecular Biology of Cancer: Mechanisms, Targets, and Therapeutics 2000
Signals, Systems, and Signal Processing 510
Discrete-Time Signals and Systems 510
Brittle Fracture in Welded Ships 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5943815
求助须知:如何正确求助?哪些是违规求助? 7089399
关于积分的说明 15892344
捐赠科研通 5075185
什么是DOI,文献DOI怎么找? 2729613
邀请新用户注册赠送积分活动 1689187
关于科研通互助平台的介绍 1614170