Predictive Maintenance 4.0 for Chilled Water System at Commercial Buildings: A Methodological Framework

被引:8
作者
Almobarek, Malek [1 ]
Mendibil, Kepa [1 ]
Alrashdan, Abdalla [2 ]
机构
[1] Univ Strathclyde, Fac Engn, Dept Design Mfg & Engn Management, Glasgow G1 1XQ, Scotland
[2] Alfaisal Univ, Coll Engn, Ind Engn Dept, Riyadh 50927, Saudi Arabia
关键词
predictive maintenance; Industry; 4; 0; Quality; decision tree algorithm; chilled water system; HVAC; commercial buildings; industrial engineering; engineering management; FAULT-DETECTION; DIAGNOSIS; MODEL; STRATEGY;
D O I
10.3390/buildings13020497
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Predictive maintenance is considered as one of the most important strategies for managing the utility systems of commercial buildings. This research focused on chilled water system (CWS) components and proposed a methodological framework to build a comprehensive predictive maintenance program in line with Industry 4.0/Quality 4.0 (PdM 4.0). This research followed a systematic literature review (SLR) study that addressed two research questions about the mechanism for handling CWS faults, as well as fault prediction methods. This research rectified the associated research gaps found in the SLR study, which were related to three points; namely fault handling, fault frequencies, and fault solutions. A framework was built based on the outcome of an industry survey study and contained three parts: setup, machine learning, and quality control. The first part explained the three arrangements required for preparing the framework. The second part proposed a decision tree (DT) model to predict CWS faults and listed the steps for building and training the model. In this part, two DT algorithms were proposed, C4.5 and CART. The last part, quality control, suggested managerial steps for controlling the maintenance program. The framework was implemented in a university, with encouraging outcomes, as the prediction accuracy of the presented prediction model was more than 98% for each CWS component. The DT model improved the fault prediction by more than 20% in all CWS components when compared to the existing control system at the university.
引用
收藏
页数:19
相关论文
共 36 条
[1]   On Predictive Maintenance in Industry 4.0: Overview, Models, and Challenges [J].
Achouch, Mounia ;
Dimitrova, Mariya ;
Ziane, Khaled ;
Karganroudi, Sasan Sattarpanah ;
Dhouib, Rizck ;
Ibrahim, Hussein ;
Adda, Mehdi .
APPLIED SCIENCES-BASEL, 2022, 12 (16)
[2]  
Almobarek M., 2022, TOTAL QUAL MANAG BUS, V14, P86, DOI [10.1504/IJSSCA.2022.124971, DOI 10.1504/IJSSCA.2022.124971]
[3]  
Almobarek M., 2022, P 12 INT C IND ENG O, P1616
[4]  
Almobarek M., 2021, P 11 INT C IND ENG O, P1509
[5]   Fault Types and Frequencies in Predictive Maintenance 4.0 for Chilled Water System at Commercial Buildings: An Industry Survey [J].
Almobarek, Malek ;
Mendibil, Kepa ;
Alrashdan, Abdalla ;
Mejjaouli, Sobhi .
BUILDINGS, 2022, 12 (11)
[6]   Predictive Maintenance 4.0 for Chilled Water System at Commercial Buildings: A Systematic Literature Review [J].
Almobarek, Malek ;
Mendibil, Kepa ;
Alrashdan, Abdalla .
BUILDINGS, 2022, 12 (08)
[7]  
[Anonymous], ASHRAE HDB
[8]  
Bacon M., 2012, Pragmatism: An introduction
[9]  
Beckmann C., 2004, LECT NOTES COMPUT SC
[10]   Predictive Maintenance in the 4th Industrial Revolution: Benefits, Business Opportunities, and Managerial Implications [J].
Bousdekis A. ;
Apostolou D. ;
Mentzas G. .
IEEE Engineering Management Review, 2020, 48 (01) :57-62