Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/13611
Title: Maintainability of facades in the tropics: An ANN model for maintainability grading
Authors: TAN PHAY PING
Keywords: defects, risk analysis, neural networks, facade maintainability, performance evaluation, life cycle cost
Issue Date: 27-Feb-2004
Source: TAN PHAY PING (2004-02-27). Maintainability of facades in the tropics: An ANN model for maintainability grading. ScholarBank@NUS Repository.
Abstract: In Singapore, maintenance costs have been identified to make up 59% and 44% of overall operational cost of Housing Development Board (HDB) estates and private condominiums respectively (BCA pilot study report, 2000). The annual maintenance expenditure for residential buildings has risen sharply from S$10.80/m2 in 1989 to S$37.99/m2 in 2000 (The Construction a??90; Pilot Study Report by BCA, 2000). Of this, facade maintenance to remedy defects makes up a sizable portion. This could be well illustrated from the web-based defects library (www.hpbc.bdg.nus.edu.sg) compiled for this study. It is hence necessary to improve the level of maintainability right from the design stages. In this study, 450 buildings in Singapore were evaluated to identify facade defects and establish causes that determine the defectsa?? severity and occurrence. Using artificial neural networks, a facade maintainability scoring system was then developed to provide a predictive indication of the extent of cleaning, repairs and replacements required in its whole life. 22 major risk factors relating to facade design, construction, maintenance and environment were used as inputs for model construction. The framework may serve as a practical tool for building professionals in achieving maintainable designs and optimum maintenance strategies for building facades right from the planning and design stages.
URI: http://scholarbank.nus.edu.sg/handle/10635/13611
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