Maintenance Analytics for Building Decision-Making: A Literature Review

Abstract

There is a prevalence of poor building maintenance practices in both the public and private sectors in Malaysia. To improve the current state of maintenance, effective decisions must be made by the building stakeholders. Unfortunately, the decision-making process for building maintenance in Malaysia is still traditional. The decisions are usually made based on the latest maintenance inspection without taking into consideration the trend of past data. This limits the building maintenance strategy to corrective (reactive) and preventive (expensive). Data-driven decisions improve building operations and create better predictive maintenance programs because the stakeholders can instantly identify problems and effectively act. Maintenance analytics is a structured and technological approach used to extract information from data and has proven to be an acceptable tool to improve building operation and maintenance. It is used to determine “what has happened?”, “why it happened?”, “what will happen?”, and “what needs to be done?” to enable decision-makers to take appropriate actions. In a country like Malaysia where maintenance practice is not data-driven, there is a need to identify the techniques to improve the maintenance process (especially decision-making). Therefore, this study aims to identify the various analytical techniques applied in existing maintenance analytics studies and determine the current direction of maintenance analytics studies. A comprehensive literature review was done to understand maintenance analytics, types of data and its sources, and the analytical techniques applied. Findings from the literature review revealed that the major data sources are CMMS, BIM, IoT, BAS. It was also noticed that the type of data used influenced the choice of analytical technical techniques. In addition, it was noted that certain studies did not use the major data sources and analytical techniques, and other studies used more than one data source. Overall, the general direction of the maintenance analytics studies was building performance and operation, end-user complaints, and work orders. There is a gap in the application of maintenance analytics to cost-effective decision-making in building maintenance. Which is recommended as the direction for future studies.

Refrigerant Management by Using Iot Technology With the Co-benefit in Energy Saving at Malaysia Food and Cold Chain Sector

“…In Malaysia, the proper maintenance culture and practice is very poor. Whereas, the maintenance activity is only done in an emergency or severe fault of equipment, especially when refrigeration and maintenance issues are given no priority in most organization administration (Adeyemi et al, 2022). According to the Hauashdh et al (2020), there are four key issues related with the building maintenance in Malaysia which is management, nancial, technical and human resources.…”

“…This method is not accurate as indirect method that used sensor to detect the fault of refrigeration system from inside and provide real-time data monitoring of the system. Having such information and communications technology (ICT) tool, will help facility manager and service technician to detect the accurate fault and provide an early response time on the fault Adeyemi et al, 2022;Hauashdh et al, 2022). According to the Adeyemi et al (2022), it is incredibly di cult to accurately maintain and take an early action of the system in the absence of real-time data (Adeyemi et al, 2022).…”

“…Having such information and communications technology (ICT) tool, will help facility manager and service technician to detect the accurate fault and provide an early response time on the fault Adeyemi et al, 2022;Hauashdh et al, 2022). According to the Adeyemi et al (2022), it is incredibly di cult to accurately maintain and take an early action of the system in the absence of real-time data (Adeyemi et al, 2022). Improper service maintenance practice and late response time will cause ine cient of refrigeration system, as well as can give a signi cant impact on energy e ciency.…”