All other errors and inconsistencies affect data on an
interval scale. Missing time-stamps of production processes
and missing set-up and processing times affect the
completeness dimension of data quality (b). Increasing lot
sizes over the course of one production order obviously have
to be incorrect (c). Finally, five different cases of time
overlaps between consecutive process steps lead to
inconsistencies in the datasets (d). The rate of occurrence of
these errors and inconsistencies have been examined for four
real-world industrial data sets of German mid-sized
manufacturing companies