Developing an algorithm for predictive maintenance of different components of building projects in Uganda using MS Excel software: Floorscreed and light bulbs

Abstract

There is an increasing growth in adaptation to predictive maintenance algorithms in building components in the recent years due to the fact that they have proved to be effective. The dominant explanation for this trend is increased effectiveness in ICTs. Previous research has primarily been based on the machine parts of a structure such as air conditioners for algorithm development since sensors can be employed to easily generate data such as temperature values. However, certain building components that need maintenance systems may not be able to apply sensors for data collection such as the floor finishes. Therefore, data collection is done manually for the purposes of this report to be able to generate relationships that could be used in developing an algorithm for predictive rehabilitation. The data is related with degradation factors and functions created that can return a predictive value. With enough data, any building manager is able to understand the trends in the different building components and therefore know when rehabilitation would need to be done. The data collected was input into the formula created in MS Excel. Macros are then run in VBA to create a continuous loop for returning results whenever variables change. For simplicity, the algorithm is represented as a form so that the user does not have to deal with the calculations that happen backend.