An Acquisition on Big Data Model for Quality Tracing of Iron and Steel Industries
S. Priyadharsini1, K. Ponnalagu2, E. Glory Bebina3, A.V.R. Aarthi4

1S. Priyadharsini, Assistant Professor (Mathematics), Sri Krishna Arts and Science College, Coimbatore, India.
2K. Ponnalagu, Professor (Mathematics), Sri Krishna Arts and Science College, Coimbatore, India.
3E. Glory Bebina , M.Sc. (Mathematics), Sri Krishna Arts and Science College, Coimbatore, India.
4A.V.R. Aarthi, M.Sc. (Mathematics), Sri Krishna Arts and Science College, Coimbatore, India.

Manuscript received on 02 July 2019 | Revised Manuscript received on 09 July 2019 | Manuscript published on 30 August 2019 | PP: 1780-1783 | Volume-8 Issue-10, August 2019 | Retrieval Number: J91780881019/2019©BEIESP| DOI: 10.35940/ijitee.J9178.0881019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Quality determine is essential affair for steel industries. Due to complication and variation of nature input that turn to be changed into many forms. Due to this, it is tough to explicit the report and trace over the whole product life cycle from designing, construction, etc. According to big data approach, study of the essence of steel brand and the factor of their manufacturing system and it is effective viable multi row system which consists of four structure , [1] the basis quality bill of material [BQBOM] ,[2]the general process bill of material [GPBOM],[3] the production and scheduling bill of material [PSBOM] ,[4 ]the final quality bill of material [FQBOM]. This mode would be useful to builders to frame a kind of scheme in big data production environment.
Keywords: big data , bill of material , hadoop , hdfs, mapreduce ,quality data.
Scope of the Article: Big Data Analytics