As previously written about on this blog, automated Quality Control (QC) within file-based production facilities has been regarded as a key issue for a number of years ago. Back in 2010, the EBU recognized QC as a key topic for the media industry and has subsequently stated that manual quality control processes are simply not adequate anymore and do not scale:
So, you could be forgiven to think that this would have heralded a boom period for QC tool manufacturers. However, if you look at this market more carefully that prediction does not appear accurate.
Following impressive launches and demonstrations at NAB and IBC in 2006, the potential savings in op-ex and gains in efficiency that automated QC tools offered grabbed the attention of budgeting and planning teams in media facilities worldwide. But nearly eight years later, and despite some really significant advances in their functionality, accuracy and performance of these tools, sadly, many of the automated QC tools bought and installed lie dormant or, at best, under-utilized.
The most frequently given reason for this is simply that the systems would generate so many errors across so many metrics that it was nearly impossible for a piece of media to successfully pass.
At AmberFin, we hate waste and love efficiency, so here are three simple steps to fix QC errors and make the best use of your automated QC.
1. Turn off the QC tests.
No, really! Perhaps not all of them, but work out which ones are actually going to identify real problems downstream in the workflow or presentation of the media and turn off the remainder. Just last week we were talking to a customer who was having problems with every piece media failing QC due to audio peak levels. Clearly, there could have be an issue here, but the previous step in the workflow was to normalize the audio to meet EBU R128 loudness specifications, which it did – so the peak level errors were not only spurious, but the test itself unnecessary.
2. Visualize it!
If you take the event data generated by an automated QC and present it in a clear, interactive way, it becomes much quicker and easier for operators to make sound judgments and distinguish real errors from marginal issues or “false positives” / “false negatives”. This is whyAmberFin created UQC and use it to validate our own ingest and transcode tools in iCR. The timeline gives a clear view of any problems detected and, alongside video and audio playback, makes it considerably faster and more efficient to identify genuine problems.
3. QC the workflow
Toyota gained a reputation for building hig quality cars at a low price. Their QC process did not involve a single gigantic QC operation at the end of the production line. They implemented a production system where the processes themselves were checked – the theory being that if you start with the right input and have the right processes, then the output will also be right. We can implement the same idea in media workflows by identifying issues introduced in the workflow and fixing the workflow rather than fixing individual items of media. This should, in turn, reduce the number of error events reported by automated QC tools and further increase efficiency.
Don’t let your Automated QC tool sit Idle!
If you have an Automated QC tool sitting idle and unloved, why not try these three easy steps to get closer to those promised savings and gains. If you are still trying to get your head around this important issue, then you can learn a great deal if you download AmberFin’s QCWhite Paper – Unified Quality Control from AmberFin.
