Application of industrial big data for smart manufacturing in product service system based on system engineering using fuzzy DEMATEL

Abstract

With the rapid development of information, communication, Internet and other technologies, data from all walks of life show the characteristics of explosive growth. The industrial big data is generated by the continuous infiltration of big data in industry. Industrial big data system is a tool of smart manufacturing system (SMS), which supports product service system (PSS) to increase added value for enterprises through the bridge of product life cycle oriented services. There are relatively many studies on methods, technologies and architectures of industrial big data from the perspective of data flow. However, from the specific implementation path, there are relatively few studies on the general model and implementation framework of the application of industrial big data. In particular, around the detailed application scenarios, there is no clear implementation framework for top-level design and planning of big data, which can be customized in different industries. Therefore, the system model for I-BA (Industrial Big data Application) was studied by using the method of system engineering analysis, and a general reference model of I-BA was put forward. Further, a general reference architecture of implementation path for I-BA was proposed. Then, a quantitative model and method based on fuzzy DEMATEL (Decision Making Trial and Evaluation Laboratory) for influencing factors of I-BA were proposed. Finally, a case study for I-BA in marine engineering field was given. It can provide theoretical basis for industry and government to plan, formulate and implement big data. At the same time, it can provide some reference value for upgrading and supplementing the smart manufacturing architecture.