Created on 01-04-2019 03:24 AM - edited 08-17-2019 05:03 AM
Image Data Flow for Industrial Imaging
Ingest and store manufacturing quality assurance images, measurements, and metadata in a cost-effective and simple-to-retrieve-from platform that can provide analytic capability in the future.
In high-speed manufacturing, imaging systems may be used to identify material imperfections, monitor thermal state, or identify when tolerances are exceeded. Many commercially-available systems automate measurement and reporting of specific tests, but combining results from multiple instrumentation vendors, longer-term storage, process analytics, and comprehensive auditability require different technology.
Using HDF’s NiFi and HDP’s HDFS, Hive or Hbase, and Zeppelin, one can build a cost-effective and performant solution to store and retrieve these images, as well as provide a platform for machine learning based on that data.
Sample files and code, including the Zeppelin notebook, can be found on this github repository: https://github.com/wcbdata/materials-imaging
HDF 3.0 or later (NiFi 220.127.116.11+)
HDP 2.6.5 or later (Hadoop 2.6.3+ and Hive 1.2.1+)
Spark 18.104.22.168.6.2.0-205 or later