Abstract

Building operation and maintenance costs play a key role in the total ownership costs of buildings over their lifetime. Accurate forecasting of these costs can assist owners and asset managers in making appropriate investment decisions and budget allocation. However, the accurate maintenance/repair (M/R) costs are very difficult to determine due to the uncertain maintenance/repair activities and asset conditions over the life cycle of the buildings. The present research presents a model developed to evaluate and forecast M/R costs of office buildings. This developed forecasting model considers the weights of the factors that influence the M/R costs as well as the related adjusting factors of these costs. The elements that make up the M/R costs of office buildings have been identified. Historical data of these elements published by Building Owners and Managers Association (BOMA) is adapted and analyzed. A simulation method is used to establish the probability distributions of the M/R costs. Six main factors influencing the total M/R costs and their associated elements have been defined. Analytic Hierarchy Process (AHP) method is employed to determine the weights of these influencing factors and their associated elements. A prototype FTMRC (forecast total maintenance and repair costs) system is developed to implement the proposed forecasting model. The function-oriented design method is employed to implement the system. The prototype software is coded using Visual Basic Applications and operates in a Microsoft Windows environment. There are eight components comprised in the FTMRC system. The evaluation, forecasting, and analyzing functionalities can be carried out by utilizing the proposed models and stored data. The FTMRC system also provides an analysis of the Net Present Value of M/R costs over the analyzed life span of office buildings. The FTMRC system further provides sensitivity analysis to assist users to recognize the most important variables affecting the Net Present Value of M/R costs. The system can also provide both numerical reports and graphical reports. A numerical example from real industry is utilized to validate both the proposed forecasting model and the developed prototype. Mean absolute percent error (MAPE) method is used to evaluate the accuracy of the proposed forecasting model. The validation of the developed FTMRC system shows that this prototype can perform all the proposed system tasks and can provide users with an easy and efficient tool to forecast their future M/R expenditures and to have an overall view of their budget.