  Knowledge of a machine tool axis to axis location errors allows compensation
and correcting actions to be taken to enhance its volumetric accuracy. Several
procedures exist, involving either lengthy individual test for each geometric
error or faster single tests to identify all errors at once. This study focuses
on the closed kinematic Cartesian chain method which uses a single setup test
to identify the eight link errors of a five axis machine tool. The
identification is based on volumetric error measurements for different poses
with a non-contact measuring instrument called CapBall, developed in house. In
order to evaluate the uncertainty on each identified error, a multi-output
Monte Carlo approach is implemented. Uncertainty sources in the measurement and
identification chain - such as sensors output, machine drift and frame
transformation uncertainties - can be included in the model and propagated to
the identified errors. The estimated uncertainties are finally compared to
experimental results to assess the method. It shows that the effect of the
drift, a disturbance, must be simulated as a function of time the Monte Carlo
approach. The machine drift is found to be an important uncertainty in sources
for the machine tested.
