On site big data analysis system model to promote the competiveness of manufacturing enterprises

Abstract

Small and medium-sized manufacturing enterprises are highly vulnerable to competition compared to conglomerates, as not many of them have adopted Manufacturing Execution Systems (MES) and do not have sufficient IT specialists and investment funds. In this research, therefore, a Big data analysis system model that can be used on site was developed that is practical and flexible enough to be adopted easily, thus enabling the use of Big data technology to consolidate the competitiveness of small and medium-sized manufacturing business. The on-site big data analysis system model saves the internet data into the proper Data Store according to their usage purpose after collection, including Excel data on the site of small and medium-sized manufacturing enterprises, typical and atypical files, sensor Data, and news/blogs/SNS data. The saved data supports decision making with strong visual effects, and intuitive data detectable network visualization technologies which are offered by various charts through the library of open source data visualization, D3.js. In addition, the model shows practical adaptation and flexibility through a customized plug-in method that can be adjusted to the IT environment of small and medium-sized manufacturing enterprises.