Munich Personal RePEc Archive

Ein Bayes-Netz zur Analyse des Absturzrisikos im Gerüstbau

Oepping, Hardy (2016): Ein Bayes-Netz zur Analyse des Absturzrisikos im Gerüstbau.


Download (24MB) | Preview


Falling from height while erecting a scaffold is one of the most prominent operative risks of a scaffolding company. Proper estimates of conditional fall probabilities considering all influencing factors are a crucial concern in assessing and implementing suitable risk control measures. This paper proposes an approach to designing a Bayesian network by which the following presumptions can be reviewed:

1. The risk of falling from height is more sensitive to length than to height of a scaffold 2. Project staff changes during running projects generally increase fall probability 3. The fall probability decreases systematically as the erecting process progresses

These presumptions will be discussed and scrutinised on the basis of a Bayesian network that provides suitable hypotheses about the relations between fall probability and its most relevant influencing factors. Theoretical implications, occurring problems, and present solutions in designing and applying the risk model will be presented in detail.

Atom RSS 1.0 RSS 2.0

Contact us: mpra@ub.uni-muenchen.de

This repository has been built using EPrints software.

MPRA is a RePEc service hosted by Logo of the University Library LMU Munich.