2.1. Smart Manufacturing System
The current manufacturing environment faces many critical challenges. Demanders continuously require highly customized products for their various needs(S. Wang, Wan, Zhang, Li, & Zhang, 2016). Also, the increase in labor costs has weakened production competitiveness. In addition, there are strict regulations on the manufacturing industry because of environmental problems such as global warming and environmental pollution. In this situation, to overcome the current facing difficulties, the manufacturing industry is aiming to improve competitiveness through the convergence with cutting-edge ICT(Information and communication technology) technologies(Kang et al., 2016). Smart manufacturing that maximizes production competitiveness by combining with latest ICT technology has received attention. Wallace and Riddick (2013) described smart manufacturing as a data intensive application of information technology at the shop floor level and above the enable intelligent, efficient, and responsive operation.
Existing manufacturing system have been consistently converged with ICT even before advent of smart manufacturing, such as realizing digital manufacturing. Beyond these efforts, smart manufacturing has attempt to combine more diverse and cutting-edge technologies with exiting manufacturing for its performance. Up until now, most systems in the manufacturing industry were used as a tool for managing enterprise resources, gathering outdated data and visualizing them. However, recently smart manufacturing system has combined with cutting-edge sensing and controlling devices, while also analyzing big-data using machine learning. This allows them to actually provide information helpful to the decision making process or directly design and carry out the manufacturing process at the shop floor level. Therefore in this research, smart manufacturing system is defined as an information system actively and directly involved in the conducting manufacturing process by gathering and analyzing real-time data gathered from field devices, while also making decisions based on algorithms in order to meet the changing demands and conditions in the factory.