The rate of data growth in the manufacturing industry exceeds the capacity of conventional manufacturing information systems. Recently, big data analysis is considered to enhance the existing systems to extract an insight from the large-scale shop floor data. However, there remain a lot of unsolved, practical problems that the existing systems have not taken account of. In this paper, we propose a large-scale data management system to integrate the set of manufacturing data with regard to four common elements: machine, material, method, and man. Additionally, we suggest a novel problem to trace production logs without any linkage between materials and products. Our ultimate goal is developing an information system for predictive manufacturing, which can capture, in advance, potential risk factors, such as machine worn out progress and production time loss tendency. The work is expected to meet the visions of emerging innovative projects for the future manufacturing industry.
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