• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.329-331
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• 2018

In this paper, we propose a monitoring system that starts with the supply of raw materials for threading, is processed into a lathe machine, and checks for defects of the product are automatically performed by the robot with Smart Factory technology through assembly and disassembly. Completion check according to the production instruction quantity and production instruction is made by checking the production status according to whether or not the raw material is worn by the displacement sensor, and checking the pitch and the contour of the processed female and male to determine OK and NG. The robotic system acts as a relay for loading and unloading of raw materials, pallet transfer, and overall process, and it acts as an intermediary for organically driving. The location information of the threaded products is collected by using the non-contact wireless tag and the energy saving system Production efficiency and utilization rate were checked. The environmental sensor collects the air-conditioning environment data (temperature, humidity), measures the temperature and humidity accurately, and checks the quality of product processing. It monitors and monitors the driving hazard level environment (overheating, humidity) of the product. Controls for CNC and robot module PLC as a heterogeneous system.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.230-238
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• 2023

Small and medium-sized food manufacturing enterprises are largely reliant on manual labor, from inputting raw materials to palletizing the final product. Recently, there has been a trend toward smartness and digitization through the implementation of robotics and sensor data technology. In this study, we examined the effectiveness of improvement through 3D simulation on two repetitive work processes within a food manufacturing company. These processes involve workers whose speed cannot match the capacity of the applied equipment. Two manual processes were selected: the weighing and packing process performed by workers after skewer assembly, and the manual batch process of counting randomly delivered frozen foods, packing (both internal and external), and palletizing. The production volume, utilization rate, and number of workers were chosen as verification indicators. As a result of the simulation for improving the 3D process, production increased by 13.5% and 56.8% compared to the existing process, respectively. This was particularly evident in the process of applying palletizing robots. In both processes, as the utilization rate and number of input workers decreased, robots could replace tasks with high worker fatigue, thereby reducing work overload. This study demonstrates the potential to visually compare the process flow improvement using 3D simulations and confirms the possibility of pre-validation for improvement.