Abstract:
The research into the issue of maintainability of multi-story buildings in Sri Lanka is still in
its adolescent stage. This report summarizes the main deliverables of a research project
dealing with maintainability of multi-story buildings using two elements; fa9ade and flat roof,
under tropical conditions. Improving the knowledge of maintainability and setting
maintainability benchmarks are two key principles of the research framework.
In identifying maintainability problems, 26 and 16 numbers of different defects were
identified related to facade and flat roof defects respectively. Their causes were identified as
faulty designs, inferior construction and ad-hoc maintenance practices. They were taken as
maintainability risk factors for both maintainability scoring systems.
The existing maintainability scoring system developed by National University of Singapore
(NUS-MSS) was tested for its adoptability for multi-story buildings in Sri Lanka due to
similarity between environment and buildings profiles in two countries. Statistical /-test was
used for the comparison. This model was developed using 13 risk factors related to fa5ade
maintainability. These factors are common for maintainability of facades of multi-story
buildings here. Further, statistical test results showed that NUS-MSS can be successfully
adopted to predict the level of maintainability of fa9ades of multi-story buildings in Sri
Lanka
A prototype maintainability scoring system for flat roof using the framework of NUS-MSS;
on the basis of life cycle costing approach, involving minimum cleaning, repair, replacement
and down time, is established using the back propagation neural networks. This system
compromised of 12 input risk factors related to flat roof maintainability including building
profile, design parameters, choice of materials, quality of construction, maintenance practices,
and environment. Low errors of “network” and “generalization” of the network indicated its
capability of forecasting the maintainability levels for new designs. Therefore, as a predictive
tool, this system would enable owners, designers, facility managers, contractors and any other
party with an interest in achieving the most favourable maintainability right from the
design/planning stage.
