An Acquisition On Big Data Model For Quality Tracing Of Iron And Steel Industries | Zendy

S. Priyadharsini | Zendy; Karthikeyan Ponnalagu | Zendy; E. Glory Bebina | Zendy; A.V.R. Aarthi | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

An Acquisition On Big Data Model For Quality Tracing Of Iron And Steel Industries

Author(s) -

S. Priyadharsini,

Karthikeyan 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) , computer science , big data , scheduling (production processes) , product (mathematics) , process (computing) , manufacturing engineering , production cycle , industrial engineering , engineering , operations management , data mining , mathematics , economics , 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

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research