This paper addresses the problem of diagnosability analysis in Web Services. In particular, it focuses on the analysis of the impact of time to the diagnostic capabilities in Web Service workflows. The diagnosability analysis that is proposed in this paper aims at determining the diagnostic capabilities of a previously developped algorithm for the diagnosis of Web Services. This diagnostic algorithm is based on chronicle recognitions. Faults that can occur during the execution of service workflows are described by means of chronicles. To perform this diagnosability analysis, the problem is firstly defined as a languagebased analysis which leads to the definition of exclusiveness tests between the languages represented by the chronicles. To deal with the time aspects inherent to the chronicles, we then propose to perform the automatic analysis by the use of time Petri nets. Exclusiveness tests are then defined on reachability graphs of time Petri nets which implicitly represent chronicle languages.