A Data-Driven Condition Monitoring of Product Quality Analysis System Based on RS and AHP
Mechanical and electrical products have complex structure and intelligent control system, their reliability plays an important role in the normal operation of security facilities. However, most manufacturers usually pay more attention to the product designing and manufacturing quality, with little i...
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Format: | Article |
Language: | English |
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Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek
2020-01-01
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Series: | Tehnički Vjesnik |
Subjects: | |
Online Access: | https://hrcak.srce.hr/file/343900 |
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author | Jihong Pang Ruiting Wang Quan Xiao Feifei Qin |
author_facet | Jihong Pang Ruiting Wang Quan Xiao Feifei Qin |
author_sort | Jihong Pang |
collection | DOAJ |
description | Mechanical and electrical products have complex structure and intelligent control system, their reliability plays an important role in the normal operation of security facilities. However, most manufacturers usually pay more attention to the product designing and manufacturing quality, with little interest in the intelligent fault diagnosis. The objective of this study is to develop the products quality intelligent analysis and management system based on Rough Set (RS) and Analytic Hierarchy Process (AHP). Firstly, this paper reviews the principle of hardware, software design, monitoring platform and quality analysis system to reduce the number of information transfer with computer technology. Secondly, the fault types and feature extractions of different faults of elevators are presented and simplified by using RS theory. Then, the objective weight of level index model can be obtained by AHP method, and the comprehensive analysis weight of each index is obtained by using the value of subjective and objective weight coefficients with the golden ratio. Finally, a comprehensive decision weight of the major index for quality control analysis system of many vertical elevators is presented. The results show that the data-driven condition monitoring and quality analysis system is a kind of important means to prevent a disaster of complex mechanical and electrical products. |
first_indexed | 2024-04-24T09:20:10Z |
format | Article |
id | doaj.art-3c35982adee94e81993b0f06ff656610 |
institution | Directory Open Access Journal |
issn | 1330-3651 1848-6339 |
language | English |
last_indexed | 2024-04-24T09:20:10Z |
publishDate | 2020-01-01 |
publisher | Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek |
record_format | Article |
series | Tehnički Vjesnik |
spelling | doaj.art-3c35982adee94e81993b0f06ff6566102024-04-15T16:07:59ZengFaculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in OsijekTehnički Vjesnik1330-36511848-63392020-01-0127238239010.17559/TV-20190828170533A Data-Driven Condition Monitoring of Product Quality Analysis System Based on RS and AHPJihong Pang0Ruiting Wang1Quan Xiao2Feifei Qin3College of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou 325035, P. R. ChinaCollege of Mechanical and Electrical Engineering, Wenzhou University, Wenzhou 325035, P. R. ChinaSchool of Information Management, Jiangxi University of Finance and Economics, Nanchang 330032, P.R. ChinaSchool of Information Science and Engineering, Wenzhou Business College, Wenzhou 325035, P. R. ChinaMechanical and electrical products have complex structure and intelligent control system, their reliability plays an important role in the normal operation of security facilities. However, most manufacturers usually pay more attention to the product designing and manufacturing quality, with little interest in the intelligent fault diagnosis. The objective of this study is to develop the products quality intelligent analysis and management system based on Rough Set (RS) and Analytic Hierarchy Process (AHP). Firstly, this paper reviews the principle of hardware, software design, monitoring platform and quality analysis system to reduce the number of information transfer with computer technology. Secondly, the fault types and feature extractions of different faults of elevators are presented and simplified by using RS theory. Then, the objective weight of level index model can be obtained by AHP method, and the comprehensive analysis weight of each index is obtained by using the value of subjective and objective weight coefficients with the golden ratio. Finally, a comprehensive decision weight of the major index for quality control analysis system of many vertical elevators is presented. The results show that the data-driven condition monitoring and quality analysis system is a kind of important means to prevent a disaster of complex mechanical and electrical products.https://hrcak.srce.hr/file/343900analytic hierarchy processdata-driven condition monitoringfault informationmechanical and electrical productsquality analysis systemrough set |
spellingShingle | Jihong Pang Ruiting Wang Quan Xiao Feifei Qin A Data-Driven Condition Monitoring of Product Quality Analysis System Based on RS and AHP Tehnički Vjesnik analytic hierarchy process data-driven condition monitoring fault information mechanical and electrical products quality analysis system rough set |
title | A Data-Driven Condition Monitoring of Product Quality Analysis System Based on RS and AHP |
title_full | A Data-Driven Condition Monitoring of Product Quality Analysis System Based on RS and AHP |
title_fullStr | A Data-Driven Condition Monitoring of Product Quality Analysis System Based on RS and AHP |
title_full_unstemmed | A Data-Driven Condition Monitoring of Product Quality Analysis System Based on RS and AHP |
title_short | A Data-Driven Condition Monitoring of Product Quality Analysis System Based on RS and AHP |
title_sort | data driven condition monitoring of product quality analysis system based on rs and ahp |
topic | analytic hierarchy process data-driven condition monitoring fault information mechanical and electrical products quality analysis system rough set |
url | https://hrcak.srce.hr/file/343900 |
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