• Journal of the Korea Convergence Society
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• v.10 no.2
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• pp.67-73
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• 2019

The blood pressure measurement is calculated as a value corresponding to the pressure of the blood vessel using the pressure from the outside for a long time. Due to the recent miniaturization of measurement equipment and the ICT combination of personal healthcare systems, a system that enables continuous and real-time measurement of blood pressure with a sensor is required. In this study, blood pressure was measured using pulse transit time using Photoplethysmography. In this study, blood pressure was estimated by using systolic blood pressure. And it is possible to make measurement only with PPG itself, which can contribute to making a micro blood pressure measuring device. As a result, systolic blood pressure and PPG's S1-P and P-S2 were used to analyze the possibility of blood pressure estimation.

• Journal of Convergence for Information Technology
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• v.9 no.8
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• pp.134-139
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• 2019

This paper describes the effect of multiple signal regeneration in quadrature digital radio frequency memory(DRFM). Single channel DRFM have good reproducibility after storing a single signal. However, when reproduced after storing multiple signals, the spurious signal is large. The quadrature DRFM consists of I and Q channels, which can greatly reduce the spurious signal. The amplitude of the spurious signal depends on the number of bits of data stored in the DRFM. In this paper, we have obtained the number of bits of signal regeneration according to the application of radio frequency memory by obtaining the size of the spurious signal according to the number of bits of the stored data of the DRFM for multiple signals. As a result of this study, 4 bits quadrature DRFM can achieve a spurious output of less than -20dB, which is used for 4 signals. Those are expected to greatly contribute to the signal analysis of electronic warfare equipment and the development of jamming device.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.25-38
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• 2019

This study is to develop a diagnostic model for the effective introduction of smart factories in the manufacturing industry, to diagnose SMEs that have difficulties in building their own smart factory compared to large enterprise, to identify the current level and to present directions for implementation. IT, AT, and OT experts diagnosed 18 SMEs using the "Smart Factory Capacity Diagnosis Tool" developed for smart factory level assessment of companies. They analyzed the results and assessed the level by smart factory diagnosis categories. Companies' smart factory diagnostic mean score is 322 out of 1000 points, between 1 level (check) and 2 level (monitoring). According to diagnosis category, Factory Field Basic, R&D, Production/Logistics/Quality Control, Supply Chain Management and Reference Information Standardization are high but Strategy, Facility Automation, Equipment Control, Data/Information System and Effect Analysis are low. There was little difference in smart factory level depending on whether IT system was built or not. Also, Companies with large sales amount were not necessarily advantageous to smart factories. This study will help SMEs who are interested in smart factory. In order to build smart factory, it is necessary to analyze the market trends, SW/ICT and establish a smart factory strategy suitable for the company considering the characteristics of industry and business environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.1-6
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• 2020

Road movement pollutant air environment big data is a link between real-time traffic data such as vehicle type, speed, and load using AVC, VDS, WIM, and DTG, which are always traffic volume survey equipment, and road shape (uphill, downhill, turning section) data using GIS. It consists of traffic flow data. Also, unlike general data, a lot of data per unit time is generated and has various formats. In particular, since about 7.4 million cases/hour or more of large-scale real-time data collected as detailed traffic flow information are collected, stored and processed, a system that can efficiently process data is required. Therefore, in this study, an open source-based data parallel processing performance optimization study is conducted for the visualization of big data in the air environment of road transport pollution.

• Journal of Drive and Control
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• v.17 no.4
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• pp.125-132
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• 2020

The objective of this study was to analyze the axle load of a rice transplanter when planting rice seedlings at different working load conditions to select a suitable gear stage and a constant planting depth for rice seedlings. In this study, there are four levels of planting distances (26, 35, 43, and 80 cm) and three planting depths (low, medium, and high) with two gear stages (1.3 and 1.7 m/s). Axle loads and required planting pressures were analyzed statistically. It was observed that axle torques were increased with increasing planting depths for both gear stages, meaning that axle torques were directly proportional to planting depths for both gear stages. It was also observed that required planting pressures had a significant difference between planting distances. Planting pressures also showed significant difference according to gear stage and planting depth. These results indicate that planting pressures were directly proportional to both gear stage and planting depth. Results revealed that the automatic depth control system of a rice transplanter could not guarantee a constant planting depth as supplied pressures were variable. This indicates that a control algorithm is needed to ensure a constant planting depth. In the future, a control algorithm will be developed for an automatic depth control system of a rice transplanter to improve its comprehensive performance and efficiency.

• Journal of Drive and Control
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• v.17 no.4
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• pp.141-151
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• 2020

The aim of this study was to analyze the safety factor of range-shift gear pairs on multi-purpose agricultural implement machinery for an optimal design of a transmission system. Gear-strengths such as bending and contact stress and safety factors were analyzed under three load conditions: an equivalent engine torque at plow tillage, a rated engine torque, and the maximum engine torque. Root and contact safety factor were calculated to be 3.88, 5.14, 2.24, 2.11, 2.21, 0.99 and 0.78, 0.94, 0.65, 0.68, 0.84, 0.85, respectively, under equivalent engine torque condition at the plow tillage. The root and contact safety factor were calculated to be 1.91, 2.53, 1.10, 1.04, 1.07, 0.48 and 0.55, 0.66, 0.46, 0.48, 0.59, 0.59, respectively, under rated engine torque condition. The root and contact safety factor were calculated to be 1.60, 2.11, 0.92, 0.87, 0.90, 0.40 and 0.51, 0.61, 0.42, 0.44, 0.54, 0.54, respectively, under the maximum engine torque condition. The multi-purpose agricultural implement machinery could be conducted under plow tillage operation. However, gear specifications for tooth surface need modification because the gear surface would be broken at all driving conditions as safety factors are lower than 1.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.208-219
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• 2021

In the era of the 4th industrial revolution driven by the convergence of ICT(information and communication technology) and manufacturing, research on smart factories is being actively conducted. In particular, the manufacturing industry prefers smart factories that autonomously connect and analyze data. For the efficient implementation of smart factories, it is essential to have an integrated production system that vertically integrates separately operated production equipment and heterogeneous S/W systems such as ERP, MES. In addition, it is necessary to double-verify production data by using automatic data collection technology so that the production process can be traced transparently. In this study, we want to show a case of data-centered integration of a large aircraft parts processing factory that requires high precision, takes a long time, and has the characteristics of processing large raw materials. For this, the components of the data-oriented integrated production system were identified and the connection structure between them was explained. And we would like to share the experience gained through the design and implementation case. The integrated production system proposed in this study integrates internal components based on data, which is expected to serve as a basis for SMEs to develop into an advanced stage, and traces materials with RFID technology.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1495-1504
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• 2021

An ultra-compact binary power generation plant converts thermal energy into electric power using temperature difference between heat source and cooling source. In the actual power generation environment, the characteristic value of the plant changes due to any negative effects such as environmental condition or corrosion of related equipment. If the characteristic value of the plant changes, it may lead to unstable output of the turbine in a conventional PID control system with fixed PID parameters. A Neuro PID control system based on Neural Network adaptively to adjust the PID parameters according to the change in the characteristic value of the plant is proposed in this paper. Discrete-time transfer function models to represent the dynamic characteristics near the operating point of the investigated plant are deduced, and a design strategy of the proposed control system is described. The proposed Neuro PID control system is compared with the conventional PID control system, and its effectiveness is demonstrated through the simulation results.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.1
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• pp.27-38
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• 2023

How the port, shipping, shipbuilding, and vender industries in Korea can have a seamless value chain through their digitally smooth cooperation by applying the latest information and communications technology through the "4th industrial revolution" was examined. Also considered was the proposition that the value chain should be a smart, seamless value chain among industries with successful hyperconnection. Their cooperative relationships were defined, and the crucial elements for the sustainable development of these industries were considered. As a result, the direction for achieving environmental, social, and governance management by realizing decarbonization through today's digitalization could be studied. In particular, the importance of digitization as a way to respond to the future market from the perspective of small and medium-sized enterprises and the role of digitization realized by small and medium-sized equipment companies in the overall industry were examined. The results simultaneously show the state of linkage between industries and the reason why the value chain must maintain a smooth relationship. In addition, using the lessons learned from recent failure cases from the Korean shipbuilding industry as a cornerstone, the direction for creating a strategic pathway for intelligent connection was investigated.

• Information Systems Review
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• v.19 no.2
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• pp.95-113
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• 2017

The advent of information communication technology or the Fourth Industrial Revolution facilitated the fusion of equipment and management systems, such as Manufacturing Execution System, Enterprise Resource Planning, and Product Lifecycle Management, in the successful implementation of smart factories. The government supports the early adoption of these systems in small and medium companies to enhance their global competitiveness in producing products that can be recognized in a dramatically changing manufacturing environment. This study introduces smart factories to improve company competitiveness and address influences from the government assistance, CEO leadership, external consultancy, and organizational participation. We analyzed 101 results received from the questionnaires circulated to small- and medium-sized manufacturing companies. Given a successful smart factory implementation, company competitiveness is the factor that mostly influences organizational participation, government assistance, external consultancy, and CEO leadership. This study suggests several perspectives to implement a smart factory, which is the most important aspect of company competitiveness.