The information generated by machine vision systems puts a whole new spin on the term “big data.” The raw image files output from vision systems are huge, and manufacturers can generate terabytes of image data in a month—even in a week! So, what do you do with all this data?
Those big, fat raw image files need only be stored if the intention is to reprocess them. If the primary need is to maintain an archive of images only for compliance purposes, storage needs can be dramatically reduced by reducing file size. This can be accomplished by changing resolution or using a compressed format. An image can be reduced to a tenth the size of the raw original, or even less, and the naked eye can barely notice a difference.
Getting your files into a central database will make them more accessible and manageable. This requires a network architecture for data transfer to get the files out of that inspection station silo. It could be a wireless network or a fixed Ethernet connection.
In order to access reliable, real-time image data transfer, you’ll require a software gateway that can do the following:
An archive is not a backup of your data. It’s a means of keeping the production data repository at a consistent size with the flexibility to “slice” the data into meaningful buckets—such as blocks of one, two, or three months, to make it easy to rotate older data into longer term storage.
This archive must be capable of storing terabytes of data in a way that supports easy and intuitive search and retrieval for rapid analysis. This means serialization—all datasets indexed by the serial number of the part/assembly to which they belong.
Inconsistency in how data is tracked and managed can be a huge problem for manufacturers. Data must be stored in the same way, using the same types of data across the plant and/or enterprise in order to be easily accessed and put to use when a situation arises.
We have worked with companies in this situation. It was taking them days to troubleshoot quality issues using custom query tools to identify the problems. If everything had been indexed by part/assembly serial number (a birth history record), days would be reduced to hours, if not minutes—without the need for custom query tools.
Have a clear archival policy because you never know when that vision data from six, 12 or even 18 months ago might become vitally important when faced with a flood of warranty claims or a recall.
A clear retention policy must be determined before data collection begins because it will drive a number of requirements, such as the IT department procuring the necessary space and resources for data storage. You need to be proactive, not reactive, to ensure a smooth rollout.
Examples of potential policies:
To learn more about machine vision and data analysis on the modern production line, download our free ebook: "How to use machine vision for manufacturing 4.0".
Sciemetric offers solutions for process monitoring, learn more about the sigPOD and Sciemetric Edge.