Exploring the research trend of smart factory with topic modeling

Abstract

Growing competition among manufacturing businesses and the advent of the Fourth Industrial Revolution has meant that many countries are conducting various research projects to understand how to introduce and populate smart factories. Smart factories are expected to provide a way of solving the manufacturing industries' complex problems, to take a role in breakthroughs in factories and to carry on a sustainable business. Smart factories are currently in the introduction stage, so we should follow up on the majorities and check their tendencies. However, smart-factory research is an interdisciplinary field that should be studied by researchers with diverse backgrounds in various domains. Thus, studying the past and present overall research trends of smart factory studies is required for their successful introduction and sustainable research. In this study, we explored the research trends of smart factories in both international and specifically Korean research, as an example of a nation case, to determine the major research directions. We determined trends using latent semantic analysis, which is a known topic-modeling technique, and analyzed the trends with regression-based methods. As a result, we could read the clear trends by analyzing existing studies related to smart factories. In addition, it is possible to compare research trends in Korea and international research trends for the commonly appeared topics, such as 'ICT' (Information and Communications Technology) and 'R & D (Research and Development)/Technology Innovation'. We expect that the quantitative analysis results and suggestions presented in this study can be used to formulate strategies for the future diffusion of smart factories. © 2018 by the authors.