Modelling the running costs of buildings

Abstract

The Building Maintenance Cost Information Service (BMCIS) offers a comprehensive and rigorous framework for collecting data about the running costs of buildings. Nevertheless, it is pitched at such a level of detail that the amount of data collected and analysed may be constrained. This paper describes the deveopment and testing of a novel technique which reduces the amount of data to be collected without any unacceptable reduction in utility. It draws on the principle of cost-significance to create a simple model of maintenance and operating costs (together called running costs) from a rare and consistent set of data for 20 buildings at York University. The model contains only 11 elements, yet can predict the total running costs of each of four categories of building to an accuracy of about 21 2%. It can also predict annual costs to about 7%, despite variations in the periodicity of costs such as painting and insurance. The model was tested using the jacknife method and on virgin data. It proved to be extremely robust, predicting the running costs of 12 new buildings to within 5%. The model offers a simple framework for collecting and analysing reliable and consistent data on running costs.Life Cycle Costs, Maintenance Costs, Operating Costs, Cost-significance,

Maintenance and operation costs model for university buildings

“…Zero mean model accuracy indicates that the model does not, on average, under or overestimate the actual costs [37]. The precision of the model is determined by the scatter of the individual accuracies for a series of buildings in one category.…”

“…The accuracy (A C ) of the cost calculated using the model is the percentage difference between the cost predicted by the model and the actual costs. The closer the value of A C is to zero the more accurate is the model and it can be calculated according to the following expression [37]:…”

Visualisation of impact of time on the internal lighting of a building

“…Also, sources of data for building maintenance are overwhelmed with details that inhibit their practical use [2]. The current paper is based on the promise that the visual approach to maintenance programme development will provide a viable way for the implementation of the just-in-time method for maintenance programming.…”

Development of an Algorithm for Sustainability Based Assessment of Reservoir Life Cycle Cost Using Fuzzy Theory

“…The developed models for computing NPV can be categorized into two groups. The first group contains those models which cannot reflect the uncertainties such as those used in researches of Bromilow and Pawsey (1987), and Al-Hajj and Horner (1998). The major advantage of these models is their simplicity but they are highly dependent on data availability which makes their application in real cases difficult.…”