Скачать или смотреть Research Training - Maintenance Analytics Model for Cost Decision Making in Malaysian Buildings

Data analytics has changed the status quo in the traditional operation modes in organisations by producing information that can be used to create innovation. Similarly, its application in maintenance (maintenance analytics) has proven to be an acceptable tool to make decisions on building operation and maintenance. Maintenance decision-making has always been based on historical data like design, drawings, maintenance records, etc. However, effective maintenance analytics is dependent on the availability of real-time data and monitoring of the overall state and performance of the building. Organisations are overwhelmed by the management and transfer of data. There is also the problem of insufficient and disintegrated data which will hinder the maintenance decision-making process. Thus, restricting the facility managers to corrective or preventive maintenance. In theory, every building should be assessed, and decisions should be made on a clear maintenance plan. However, maintenance in Malaysia is heavily regulated by the costs and several studies have investigated the attainment of cost-effectiveness. Factors like maintenance prioritisation, stakeholder involvement, skilled technicians, and spare parts have been used to examine cost-effectiveness in Malaysia. None of these studies used the data-driven approach in their investigation. The concept of using maintenance analytics for cost-effective decision-making is not new to industrial maintenance. This concept is lacking in the built environment. Therefore, there is a need to identify how maintenance analytics can be applied to cost-effective decision-making.