Common quality reports in steel sheet production are length thickness profile, and length surface flatness profile. Values contained in these reports are collected during processing sheet material in various rolling mills and processing lines, and stored for each meter of processed steel sheet.
This data is crucial in establishing product quality and identifying process flaws. It is frequently stored in factories information systems on premises, where it is available for traceability and laboratory analysis. Due to size and pace of report generation, there are a lot of problems in handling these reports, and many times only aggregated reports are preserved, while raw data is kept only for a shorter period of time.
With a current state of development of cloud technologies, and trends in communications, which promise ever faster connections, and almost negligible latencies, arguments for storing such reports in raw format in the cloud are getting only stronger.
Cloud storages are affordable, and BI tools that can be utilized for large amounts of data are already tested in various Big Data projects. Due to available huge processing power, even cases with real time analysis could be considered with feedback back to production in various scenarios.