Open AccessAn Acquisition On Big Data Model For Quality Tracing Of Iron And Steel Industries
Author(s) -
S. Priyadharsini,
K. Ponnalagu,
E. Glory Bebina,
A.V.R. Aarthi
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.j9178.0881019
Subject(s) - tracing , trace (psycholinguistics) , quality (philosophy) , production (economics) , big data , computer science , manufacturing engineering , product (mathematics) , process (computing) , scheduling (production processes) , production cycle , quality management , industrial engineering , engineering , operations management , data mining , management system , economics , mathematics , philosophy , linguistics , geometry , epistemology , macroeconomics , operating system
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