Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Development of a design-for-maintainability assessment of building systems in the tropics
Abstract The lack of Design for Maintainability (DfM) leads to avoidable building component defects and unproductive building operations. This study reports on the development of a building design assessment system which predicts maintainability impacts of design alternatives. A mixed method approach was used in this study where 1372 DfM benchmarks from 404 national and international building standards were analysed qualitatively to identify benchmarks relating to 123 critical building defects. Five Bayesian Belief Networks (BBN) were developed using five-year defect data and expert judgements from 95 case buildings. Monetary quantification of results was carried out, indicating the complex relationships between DfM benchmarks and building defects to great effect. The Bayesian networks were operationally validated using scenario tests and sensitivity analysis. The predictive power of the developed system is illustrated using an application to a hypothetical case study. This novel consequence-based DfM assessment system is a decision making tool aiding in designing more maintainable building systems which are more productive in terms of materials, labour and cost.
Highlights Methodology for a design for maintainability assessment system for building designs. Novel and flexible assessment system for maintainability with global applicability. Building design decision support with forecasting expected maintenance cost. Established variable dependence between maintainability benchmarks and defects. Knowledge and evidence-based hybrid approach to building Bayesian belief networks.
Development of a design-for-maintainability assessment of building systems in the tropics
Abstract The lack of Design for Maintainability (DfM) leads to avoidable building component defects and unproductive building operations. This study reports on the development of a building design assessment system which predicts maintainability impacts of design alternatives. A mixed method approach was used in this study where 1372 DfM benchmarks from 404 national and international building standards were analysed qualitatively to identify benchmarks relating to 123 critical building defects. Five Bayesian Belief Networks (BBN) were developed using five-year defect data and expert judgements from 95 case buildings. Monetary quantification of results was carried out, indicating the complex relationships between DfM benchmarks and building defects to great effect. The Bayesian networks were operationally validated using scenario tests and sensitivity analysis. The predictive power of the developed system is illustrated using an application to a hypothetical case study. This novel consequence-based DfM assessment system is a decision making tool aiding in designing more maintainable building systems which are more productive in terms of materials, labour and cost.
Highlights Methodology for a design for maintainability assessment system for building designs. Novel and flexible assessment system for maintainability with global applicability. Building design decision support with forecasting expected maintenance cost. Established variable dependence between maintainability benchmarks and defects. Knowledge and evidence-based hybrid approach to building Bayesian belief networks.
Development of a design-for-maintainability assessment of building systems in the tropics
Ph.D. Asmone, Ashan Senel (Autor:in) / Ph.D. Chew, Michael Yit Lin (Autor:in)
Building and Environment ; 184
27.08.2020
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
A neural network approach to assessing building facade maintainability in the tropics
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