Service life prediction is an important topic in wood research, especially with regard to the Construction Products Regulation (CPR). Both laboratory tests as well as in-service performance testing is therefore essential, in combination with proper monitoring and analysis tools. A crucial concept is variability and the incorporation of variability in tests and analysis. In this paper we focus on the use of probability density functions (pdf) to describe time-to-failure in field tests as such build further on the pdf fitting as described in part I of this publication. The statistical approach elaborated here, shows that statistically sound results can be obtained even if data are censored, i.e. when for some samples the time-to-failure criterion has not been reached yet or when the exact date of failure is not known e.g. due to non-continuous monitoring, which is normally the case for field testing. Different wood species and treatments exposed in an EN 252 set-up are compared for the test site Hamburg, Germany, and illustrate how a reference product has a longer time-to-failure than e.g. pine sapwood, and shows the sharp failure of the latter. The comparison of double layer samples at different sites resulted in the calculation of acceleration factors compared to the Hamburg site. Also, acceleration factors for shaded and non-shaded set-up were calculated. Seemingly, such an analysis is valuable to rate different sites and to compare different set-ups. It is, however, important that objective and frequent monitoring is aimed at to improve the reliability of analysis and assessment of wood durability.

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