Affiliation:
1. Faculty of Management and Computer Modelling, Kielce University of Technology, 25-314 Kielce, Poland
2. Faculty of Electrical Engineering Automatic Control and Computer Science, Kielce University of Technology, 25-314 Kielce, Poland
Abstract
The building sector contributes significantly to global final energy consumption and energy-related CO2 emissions. The demand for sustainable and energy-efficient passive buildings with a minimal ecological footprint has increased due to the global energy crisis, climate change, and environmental concerns. This need can be met by constructing passive buildings. However, to develop a building that is truly passive, it is required to meet many passive house conditions, negligible for typical buildings, which increase the project complexity and pose challenges and risks threatening its successful completion. The aim of this work is to present the findings from a quantitative risk analysis in passive construction based on the results of expert surveys that were carried out using a Computer-Assisted Web Interview. Feedback from expert surveys covering the experience of 748 passive buildings projects from seven countries (Poland, Germany, Great Britain, the United States, Australia, Spain, and Austria) allowed us to access the frequency of occurrence, severity, detectability, and Risk Priority Numbers of the 32 risk factors identified in passive buildings projects. Those risk factors were identified based on literature research, risk interviews, scenario analysis, brainstorm sessions with passive buildings specialists, and our own observations of passive buildings projects. This study revealed that incorrect costing was the most frequent issue; complicated, non-compact building shapes with an unfavorable area-to-volume ratio had the highest severity of effects; the wrong interpretation of correctly prepared drawings and details obtained from the designer had the lowest detectability; and incorrect costing had the highest Risk Priority Number. In addition, this study allowed us to identify a narrow group of critical risk factors that are the most significant (have the highest RPN) and to which special attention should be paid in the risk-management process.
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