Abstract The trace element content of clinkers (and possibly of cements) can be used to identify the manufacturing factory. The Mg, Sr, Ba, Mn, Ti, Zr, Zn and V content of clinkers give detailed information for the determination of the origin of clinkers produced in different factories. However, for the analysis of such complex data there is a need for algorithmic tools for the visualization and clustering of the samples. This paper proposes a new approach for this purpose. The analytical data are transformed into a twodimensional latent space by factor analysis (probabilistic principal component analysis) and dendograms are constructed for cluster formation. The classification of South African clinkers is used as an illustrative example for the approach.