A Dynamic Big Data Model for Quality Tracing of Steel Industries

Abstract

Quality tracing is a very important issue for steel industries. Due to the complexity and variety of quality data which tends to be changed into many forms during the whole product life cycle, it is difficult to express, record and trace through the whole product life cycle from designing, manufacturing, distributing, using and disposing. In this paper, according to the Big Data theory and the analysis of the characteristics of the steel products and the feature of their manufacturing processes, a dynamic integrated Big Data model of quality for steel industries is proposed for quality tracing issues. It is a dynamically growing multi-layered structure which consists of a four phases converting procedure: 1) the basis quality bill of material(BQBOM) which represents voice of customers; 2) the general process bill of material(GPBOM) which represents the process procedures, methods, and relative parameters during the generation of the products; 3) the production and scheduling bill of material(PSBOM) which represents the production plan controls and relative quality control specifications; and 4) the final quality bill of material(FQBOM) which represents the final product quality features to be delivered to customers and users. Techniques and procedures of the realization framework is also specified in this paper. This model would be useful for developers to build a quality system in a Big Data production environment.