As the 4th industrial revolution based on ICT is progressing in the manufacturing field, interest in building smart factories that can be flexible and customized according to customer demand is increasing. To this end, it is necessary to maximize the efficiency of factory by performing an automated process in real time through a network communication between engineers and equipment to be able to link the established IT system. It is also necessary to collect and store real-time data from heterogeneous facilities and to analyze and visualize a vast amount of data to utilize necessary information. Therefore, in this study, four types of controllers such as PLC, Arduino, Raspberry Pi, and embedded system, which are generally used to build a smart factory that can connect technologies such as artificial intelligence (AI), Internet of Things (IoT), and big data, are configured. This study was conducted for the development of a program that can collect and store data in real time to visualize and manage information. For communication verification by controller, data communication was implemented and verified with the data log in the program, and 3D monitoring was implemented and verified to check the process status such as planned quantity for each controller, actual quantity, production progress, operation rate, and defect rate.

There are many difficulties in the applications of smart manufacturing technology in the era of the 4th industrial revolution. In this paper, a test bed was built to aim for acquiring smart manufacturing technology, and the test bed was designed to acquire basic technologies necessary for PLC (Programmable Logic Controller), HMI, Internet of Things (IoT), artificial intelligence (AI) and big data. By building a vehicle maintenance lift that can be easily accessed by the general public, PLC control technology and HMI drawing technology can be acquired, and by using cloud services, workers can respond to emergencies and alarms regardless of time and space. In addition, by managing and monitoring data for smart manufacturing, it is possible to acquire basic technologies necessary for embedded systems, the Internet of Things, artificial intelligence, and big data. It is expected that the improvement of smart manufacturing technology capability according to the results of this study will contribute to the effect of creating added value according to the applications of smart manufacturing technology in the future.

We have proposed a novel planar lightwave circuit (PLC) optical sensor to monitor the contamination in a flow-cell where water is continuously supplied through a water quality measurement system. We designed a PLC chip with a V-shape waveguide and the simulated its function as a sensor for monitoring contamination in a flow-cell using a numerical the FDTD (finite-difference time-domain) analysis. A novel cross type of waveguide was introduced to make the PLC chip of the V-shaped waveguide. The fabricated PLC was cut into the cross waveguide. A change in the optical propagation loss of the PLC sensor was observed after immersing the PLC sensor into city water. It was determined that the propagation loss of the PLC sensor was 3 dB at a wavelength of 1.55 μm in the city water for 15 days.