BEGIN:VCALENDAR
VERSION:2.0
METHOD:PUBLISH
BEGIN:VEVENT
ORGANIZER;CN=ESTAD 2023:mailto:info@metec-estad.com
LOCATION:Room 28
SUMMARY:Fully automated PMI using laser-based sensor (LIBS) proves its competency in steel industry  for round bar, billet and ingot
DESCRIPTION:Due to modern days automation processes inside rolling mills, the risk of material mix-ups is pretty low. However, given the rising demand for smaller production lots and the constantly growing number of steel grades, reliable material identification along the entire process chain is still one of the highest concerns. The current state-of-the technologies (e.g., spark, magnetic induction testing) fall short to guarantee a 100% reliable check at the end of the rolling process (e.g., before shipment). On the other hand, at the beginning of the rolling process, manual activities such as picking input or semi-finished material from the storage to charge into reheating furnace often leads to material mix-ups as well. Particularly, when safety-critical components are concerned, a mix-up can have catastrophic consequences (e.g. shipment cancellation, penalty charges, loss in reputation).
With fully integrated precleaning (e.g. scale, decarbonization layers), SECOPTA developed LIBS (laser-induced breakdown spectroscopy) based sensor can analyze every moving bar (bright or black) more precisely (with respect to heat/ melt shop value) at the speed of 2 m/sec. Additionally, it can check each billet or ingot before the charging of reheating furnace assuring maximum safety without any human interference. Depending on the risk of mix-up, fiberLIBS can be integrated into the existing process (e.g., finishing line, NDT line, before reheating furnace) and fully compatible with Manufacturing Execution System Systems (MES), ensuring industry 4.0, 100% mix-up testing with significantly low maintenance and operating costs.
Since 2019, SECOPTA has carried out multiple successful installations in highly reputable special steel manufacturer facilities and years of 24/7 process operation have proven that fiberLIBS can detect out-of-spec material with more than 99,9 percent reliability. The paper followed by the Estad presentation will introduce this inline LIBS-based Positive Material Identification (PMI) technology and discuss its reliability with real-life process data.

CLASS:PUBLIC
DTSTART:20230614T100000
DTEND:20230614T102000
END:VEVENT
END:VCALENDAR