Prioritizing Autonomous Maintenance System Attributes using Fuzzy EDAS Approach

被引：6

作者：

Srivastava, Priyank ^{[1
]}

Mustafa, Arsalan ^{[1
]}

Khanduja, Dinesh ^{[2
]}

Chowdhary, Sunil Kumar ^{[1
]}

Kumar, Naveen ^{[1
]}

Kartik ^{[1
]}

Shukla, Rajendra Kumar ^{[3
]}

机构：

[1] Amity Univ, Noida 201313, Uttar Pradesh, India

[2] Natl Inst Technol, Kurukshetra 136119, Haryana, India

[3] ABES Engn Coll Uttar Pradesh, Ghaziabad 201009, India

来源：

INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND DATA SCIENCE | 2020年 / 167卷

关键词：

Autonomus maintenance; Fuzzy Methodology; EDAS;

D O I：

10.1016/j.procs.2020.03.217

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

With advancement in IT enabled tools, there is paradigm shift in maintenance process to become an automated or appropriately autonomous system. For understanding system and application of IT enabled tools identification and prioritization of system attributes is essential. This paper is focused on identification of autonomous maintenance system attributes that are based on technology perspective and its prioritization using Fuzzy EDAS method. Fuzzy methodology was used to remove issues of uncertainty and vague judgments. Sensor technology and database management were identified as pertinent attributes. The prioritization results from Fuzzy EDAS were compared with fuzzy TOPSIS approach and it shows consistency. The results were shared with the management for decision making. (C) 2020 The Authors. Published by Elsevier B.V.

引用

页码：1941 / 1949

页数：9

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