  Petabytes of data are to be processed and stored requiring millions of
CPU-years in high energy particle (HEP) physics event simulation. This enormous
demand is handled in worldwide distributed computing centers as part of the LHC
computing grid. These significant resources require a high quality and
efficient production and the early detection of potential errors. In this
article we present novel monitoring techniques in a Grid environment to collect
quality measures during job execution. This allows online assessment of data
quality information to avoid configuration errors or inappropriate settings of
simulation parameters and therefore is able to save time and resources.
