Fault Types and Frequencies in Predictive Maintenance 4.0 for Chilled Water System at Commercial Buildings: An Industry Survey
Predictive Maintenance 4.0 (PdM 4.0) showed a highly positive impact on chilled water system (CWS) maintenance. This research followed the recommendations of a systematic literature review (SLR), which was performed on PdM 4.0 applications for CWS at commercial buildings. Per the SLR, and to start m...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Buildings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-5309/12/11/1995 |
| _version_ | 1797465777400446976 |
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| author | Malek Almobarek Kepa Mendibil Abdalla Alrashdan Sobhi Mejjaouli |
| author_facet | Malek Almobarek Kepa Mendibil Abdalla Alrashdan Sobhi Mejjaouli |
| author_sort | Malek Almobarek |
| collection | DOAJ |
| description | Predictive Maintenance 4.0 (PdM 4.0) showed a highly positive impact on chilled water system (CWS) maintenance. This research followed the recommendations of a systematic literature review (SLR), which was performed on PdM 4.0 applications for CWS at commercial buildings. Per the SLR, and to start making an excellent PdM 4.0 program, the faults and their frequencies must be identified. Therefore, this research constructed an industry survey, which went through a pilot study, and then shared it with 761 maintenance officers in different commercial buildings. The first goal of this survey is to verify the faults reported by SLR, explore more faults, and suggest a managerial solution for each fault. The second goal is to determine the minimum and maximum frequencies of faults occurrence, while the third goal is to verify selected operational parameters, in which their data can be used in smart buildings applications. A total of 304 responses are considered in this study, which identified additional faults and provided faults solutions for all CWS components. Based on the survey outcomes, justifiable frequencies are proposed, which can be used in creating the dataset of any machine learning model, and then to control the CWS performance. |
| first_indexed | 2024-03-09T18:26:25Z |
| format | Article |
| id | doaj.art-6e96a4140e5843d1867a46b798a167bd |
| institution | Directory Open Access Journal |
| issn | 2075-5309 |
| language | English |
| last_indexed | 2024-03-09T18:26:25Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Buildings |
| spelling | doaj.art-6e96a4140e5843d1867a46b798a167bd2023-11-24T07:51:07ZengMDPI AGBuildings2075-53092022-11-011211199510.3390/buildings12111995Fault Types and Frequencies in Predictive Maintenance 4.0 for Chilled Water System at Commercial Buildings: An Industry SurveyMalek Almobarek0Kepa Mendibil1Abdalla Alrashdan2Sobhi Mejjaouli3Department of Design, Manufacturing, and Engineering Management, Faculty of Engineering, University of Strathclyde, Glasgow G1 1XQ, UKDepartment of Design, Manufacturing, and Engineering Management, Faculty of Engineering, University of Strathclyde, Glasgow G1 1XQ, UKIndustrial Engineering Department, College of Engineering, Alfaisal University, Riyadh 50927, Saudi ArabiaIndustrial Engineering Department, College of Engineering, Alfaisal University, Riyadh 50927, Saudi ArabiaPredictive Maintenance 4.0 (PdM 4.0) showed a highly positive impact on chilled water system (CWS) maintenance. This research followed the recommendations of a systematic literature review (SLR), which was performed on PdM 4.0 applications for CWS at commercial buildings. Per the SLR, and to start making an excellent PdM 4.0 program, the faults and their frequencies must be identified. Therefore, this research constructed an industry survey, which went through a pilot study, and then shared it with 761 maintenance officers in different commercial buildings. The first goal of this survey is to verify the faults reported by SLR, explore more faults, and suggest a managerial solution for each fault. The second goal is to determine the minimum and maximum frequencies of faults occurrence, while the third goal is to verify selected operational parameters, in which their data can be used in smart buildings applications. A total of 304 responses are considered in this study, which identified additional faults and provided faults solutions for all CWS components. Based on the survey outcomes, justifiable frequencies are proposed, which can be used in creating the dataset of any machine learning model, and then to control the CWS performance.https://www.mdpi.com/2075-5309/12/11/1995predictive maintenancechilled water systemcommercial buildingsindustry 4.0quality 4.0survey |
| spellingShingle | Malek Almobarek Kepa Mendibil Abdalla Alrashdan Sobhi Mejjaouli Fault Types and Frequencies in Predictive Maintenance 4.0 for Chilled Water System at Commercial Buildings: An Industry Survey Buildings predictive maintenance chilled water system commercial buildings industry 4.0 quality 4.0 survey |
| title | Fault Types and Frequencies in Predictive Maintenance 4.0 for Chilled Water System at Commercial Buildings: An Industry Survey |
| title_full | Fault Types and Frequencies in Predictive Maintenance 4.0 for Chilled Water System at Commercial Buildings: An Industry Survey |
| title_fullStr | Fault Types and Frequencies in Predictive Maintenance 4.0 for Chilled Water System at Commercial Buildings: An Industry Survey |
| title_full_unstemmed | Fault Types and Frequencies in Predictive Maintenance 4.0 for Chilled Water System at Commercial Buildings: An Industry Survey |
| title_short | Fault Types and Frequencies in Predictive Maintenance 4.0 for Chilled Water System at Commercial Buildings: An Industry Survey |
| title_sort | fault types and frequencies in predictive maintenance 4 0 for chilled water system at commercial buildings an industry survey |
| topic | predictive maintenance chilled water system commercial buildings industry 4.0 quality 4.0 survey |
| url | https://www.mdpi.com/2075-5309/12/11/1995 |
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