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Internet of things (IOT) based air conditioner monitoring system for intelligent facility maintenance

Office buildings often consume high energy to sustain building operations such as HVAC systems. A lack of proper decision-making approaches and a lack of maintenance planning will cause higher operational costs. This paper proposes data analytics for air conditioner’s performance in laboratory by us...

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Main Authors: Yap, Zheng Yew, Mohamad Hanif Md Saad,, Shafrida Sahrani,, Kaiser Habib,, Aini Hussain,
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2023
Online Access:http://journalarticle.ukm.my/22942/1/22.pdf
http://journalarticle.ukm.my/22942/
https://www.ukm.my/jkukm/volume-3506-2023
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spelling my-ukm.journal.229422024-01-24T04:34:13Z http://journalarticle.ukm.my/22942/ Internet of things (IOT) based air conditioner monitoring system for intelligent facility maintenance Yap, Zheng Yew Mohamad Hanif Md Saad, Shafrida Sahrani, Kaiser Habib, Aini Hussain, Office buildings often consume high energy to sustain building operations such as HVAC systems. A lack of proper decision-making approaches and a lack of maintenance planning will cause higher operational costs. This paper proposes data analytics for air conditioner’s performance in laboratory by using Internet of Things (IoT)-based monitoring system to improve efficiency in facility maintenance. It provides a monitoring system, notification system and performance dashboard to enable data analytics. The data analytics methods used here are i) condition-based maintenance which includes thermal analysis and electrical analysis; and ii) Overall Equipment Effectiveness (OEE) approach. The pre-maintenance performance measured for AC-1 is adequate while AC-2 does not meet the requirement. After the reactive maintenance was performed on AC-2; there was a performance increment of 63.15%. Based on sensors data, it seems to correlate between current draw and low refrigerant. It aids facility maintenance for early failure detection, which helps in decision-making. The result from the OEE approach also suggested the same decision-making to schedule maintenance. Performance needs to balance out to leverage power consumption without hefty operational costs for maintenance strategies. In conclusion, the data analytics provide insight for the maintenance management to monitor and schedule preventive maintenance before air conditioner (AC) faults happen. Meanwhile, the modified OEE approach for ACs to measure performance takes into consideration speed to cool down air and cost to run the AC which has not been explored yet elsewhere. Penerbit Universiti Kebangsaan Malaysia 2023 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/22942/1/22.pdf Yap, Zheng Yew and Mohamad Hanif Md Saad, and Shafrida Sahrani, and Kaiser Habib, and Aini Hussain, (2023) Internet of things (IOT) based air conditioner monitoring system for intelligent facility maintenance. Jurnal Kejuruteraan, 35 (6). pp. 1487-1500. ISSN 0128-0198 https://www.ukm.my/jkukm/volume-3506-2023
institution Universiti Kebangsaan Malaysia
building Tun Sri Lanang Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Kebangsaan Malaysia
content_source UKM Journal Article Repository
url_provider http://journalarticle.ukm.my/
language English
description Office buildings often consume high energy to sustain building operations such as HVAC systems. A lack of proper decision-making approaches and a lack of maintenance planning will cause higher operational costs. This paper proposes data analytics for air conditioner’s performance in laboratory by using Internet of Things (IoT)-based monitoring system to improve efficiency in facility maintenance. It provides a monitoring system, notification system and performance dashboard to enable data analytics. The data analytics methods used here are i) condition-based maintenance which includes thermal analysis and electrical analysis; and ii) Overall Equipment Effectiveness (OEE) approach. The pre-maintenance performance measured for AC-1 is adequate while AC-2 does not meet the requirement. After the reactive maintenance was performed on AC-2; there was a performance increment of 63.15%. Based on sensors data, it seems to correlate between current draw and low refrigerant. It aids facility maintenance for early failure detection, which helps in decision-making. The result from the OEE approach also suggested the same decision-making to schedule maintenance. Performance needs to balance out to leverage power consumption without hefty operational costs for maintenance strategies. In conclusion, the data analytics provide insight for the maintenance management to monitor and schedule preventive maintenance before air conditioner (AC) faults happen. Meanwhile, the modified OEE approach for ACs to measure performance takes into consideration speed to cool down air and cost to run the AC which has not been explored yet elsewhere.
format Article
author Yap, Zheng Yew
Mohamad Hanif Md Saad,
Shafrida Sahrani,
Kaiser Habib,
Aini Hussain,
spellingShingle Yap, Zheng Yew
Mohamad Hanif Md Saad,
Shafrida Sahrani,
Kaiser Habib,
Aini Hussain,
Internet of things (IOT) based air conditioner monitoring system for intelligent facility maintenance
author_facet Yap, Zheng Yew
Mohamad Hanif Md Saad,
Shafrida Sahrani,
Kaiser Habib,
Aini Hussain,
author_sort Yap, Zheng Yew
title Internet of things (IOT) based air conditioner monitoring system for intelligent facility maintenance
title_short Internet of things (IOT) based air conditioner monitoring system for intelligent facility maintenance
title_full Internet of things (IOT) based air conditioner monitoring system for intelligent facility maintenance
title_fullStr Internet of things (IOT) based air conditioner monitoring system for intelligent facility maintenance
title_full_unstemmed Internet of things (IOT) based air conditioner monitoring system for intelligent facility maintenance
title_sort internet of things (iot) based air conditioner monitoring system for intelligent facility maintenance
publisher Penerbit Universiti Kebangsaan Malaysia
publishDate 2023
url http://journalarticle.ukm.my/22942/1/22.pdf
http://journalarticle.ukm.my/22942/
https://www.ukm.my/jkukm/volume-3506-2023
_version_ 1789425779557269504
score 13.211869

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