Journal of the Korean Society for Precision Engineering

Prototype Development of a Smart Personal Protective Respirator with a Color-signaling Triage System: Enhancing Disaster Response through Real-time Biometric Monitoring: Dasom Koo, Joonhwa Choi, JinKi Min, Huijae Park, Dohyung Kim, Seung Hwan Ko, Jooeun Ahn, Juyeon Park; J. Korean Soc. Precis. Eng. 2025;42(11):909-917.
Published online November 1, 2025; DOI: https://doi.org/10.7736/JKSPE.025.068

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This study presents a self-wearable smart personal protective respirator featuring a color-signaling triage system designed to facilitate rapid assessment during large-scale physical disasters. The device enables individuals to wear the respirator, allowing responders to quickly identify critically ill patients through real-time biometric signal acquisition and intuitive LED-based visualization. Clinical triage criteria, developed with input from emergency medicine experts, informed a severity classification algorithm based on heart rate, respiratory rate, body temperature, and posture. To implement this system, an ergonomic head-type respirator prototype was created, integrated with a compact sensor module that includes a photoplethysmography (PPG) sensor, a barometric pressure and temperature sensor, and a combined accelerometer and gyroscope sensor. Additionally, custom sensors were developed: a respiration sensor utilizing nickel oxide nanoparticles patterned by laser, and an ECG sensor made by spraying silver nanoparticles onto a flexible polyimide film and then laser-patterning it into a serpentine shape. The system effectively detects vital signs and visualizes severity levels using color signals. Although field deployment was not part of this study, the prototype demonstrated potential to reduce triage time and enhance disaster response efficiency. Further validation in real-world settings is recommended.

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Cutting Force Monitoring Considering Electrical Characteristics of Spindle Motor: Jae-Eun Kim, Jun-Young Oh, Beomsik Sim, Wonkyun Lee; J. Korean Soc. Precis. Eng. 2025;42(1):19-25.
Published online January 1, 2025; DOI: https://doi.org/10.7736/JKSPE.024.095

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The importance of cutting forces in machining has been emphasized for monitoring and optimizing cutting conditions, leading to various method to detecting cutting forces researched. Cutting forces can be directly measured using dynamometer or indirectly estimated using AE sensors and accelerometers, etc. However, these external sensors demand high costs and have accuracy limitations due to environment issues. To compensate for these drawbacks, utilizing internal signals of machine tool has been developed. Among these, using internal electrical signals of machine tool is representative. In commercial machine tools, cutting forces are often estimated through current measurements. However, due to the characteristics of the spindle motor, electrical properties such as slip, power factor, and efficiency vary with the load, resulting in relatively lower accuracy. This study introduces current-based method considering characteristics of motor and power-based method for estimating cutting forces and compare accuracy of those methods with the measurements from dynamometer respectively.

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Introduction and Trends of Time-synchronized Measurement Devices to Advance Data-driven Smart Grid Monitoring: Gyul Lee; J. Korean Soc. Precis. Eng. 2024;41(10):735-740.
Published online October 1, 2024; DOI: https://doi.org/10.7736/JKSPE.024.082

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The smart grid was initially developed to facilitate communication between operators of the electric power system (such as power generation companies and transmission system operators) and consumers within the distribution network. To implement the smart grid paradigm, time-synchronized measurement devices were developed and introduced into the electric power system. Phasor measurement units (PMUs) and waveform measurement units (WMUs) were created for wide-area transmission networks (at the high-voltage layer), while micro-PMUs were introduced for real-time state estimation in distribution networks (at the low-voltage layer). These time-synchronized measurement devices allow power system operators to monitor the operational status of power generation, transmission, and distribution infrastructure in real time. In particular, data-driven applications utilizing the measurement data can intelligentize and advance the monitoring, operation, and control of the smart grid. The capabilities of digitized high-resolution measurement and time-synchronization are the key factors that enable these contributions to the smart grid. This paper provides an introduction to time-synchronized measurement devices, outlines their specific capabilities, and explores the data-driven applications that can be implemented for advanced smart grid monitoring systems.

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The Surface Temperature Monitoring of Brake Disc in Railway Vehicle: Jeongguk Kim, Sungil Seo; J. Korean Soc. Precis. Eng. 2024;41(9):693-698.
Published online September 1, 2024; DOI: https://doi.org/10.7736/JKSPE.024.070

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In mechanical braking systems, there are hot spots on the surface of a braking disc due to thermal deformation with a high thermal gradient. Controlling such hot spots is important for extending the life of a braking disc. In this study, surface temperatures of railway brake discs were monitored using infrared (IR) thermal imaging technique. A highspeed infrared camera with a maximum speed of 380 Hz was used to monitor surface temperature changes of the braking disc. Braking tests were performed with a full-scale dynamometer. During the braking test, the surface temperature change of the braking disc were monitored using a high-speed infrared camera. Hot spots and thermal damage observed on the surface of railway brake discs during braking tests were quantitatively analyzed using infrared thermographic images. Results revealed that monitoring disc surface temperature using IR thermographic technique can be a new method for predicting surface temperature changes without installing a thermocouple inside the disc.

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Development of a Posture Recognition Deep Learning Algorithm based on Thermal Imaging for an Elderly Monitoring Systems: SangMin Nam, DongGuk Seong, YongUn Jo, DoChang Oh; J. Korean Soc. Precis. Eng. 2024;41(8):641-646.
Published online August 1, 2024; DOI: https://doi.org/10.7736/JKSPE.024.049

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Elderly monitoring systems are gaining significant attention in our increasingly aging society. Existing monitoring systems, which utilize RGB and infrared cameras, often encounter errors when recognizing human-like objects, photos, and videos as actual humans. Additionally, privacy concerns arise due to this issue. However, these challenges can potentially be overcome by employing thermal images. Thus, our study aimed to investigate the feasibility of identifying and categorizing human postures depicted in thermal images using deep learning models and algorithms. To conduct our experiment, we developed a system that utilizes a thermal pose algorithm and a convolutional neural network. As a result, we achieved an average accuracy of 88.3%, with the highest accuracy reaching 91.2%.

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Remote Diagnosis of Air Handling Unit Belt Looseness using a Smartphone based on High-accurate Calibration: Jeongmin Kim, Jin Kim, Yong-Hwa Park; J. Korean Soc. Precis. Eng. 2024;41(8):597-605.
Published online August 1, 2024; DOI: https://doi.org/10.7736/JKSPE.024.018

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Belt-pulley looseness is a crucial factor in ensuring the safe operation of machinery used in industrial applications, such as compressors and fans. Traditionally, belt looseness has been inspected using contact-based current and vibration sensors. However, these methods are time-consuming and require manual attachment of the sensors. In order to overcome the limitations of these traditional methods, we propose a remote diagnosis method for detecting belt looseness using a smartphone. By utilizing a four-mirror system, the smartphone can construct a stereo system that enables 3D reconstruction of the object. This allows us to reconstruct the 3D trajectory of the belt and diagnose the level of looseness. To further enhance the accuracy of our proposed system, we have developed a calibration algorithm specifically designed for the four-mirror system. In our actual experiment, we successfully diagnosed four levels of belt looseness. As the level of looseness increased, we observed a curved shape in the 3D trajectory of the belt, along with noticeable quantitative differences. To quantitatively analyze these differences, we introduced a measure called the residual, which reflects the curvilinearity of the 3D trajectory. Our findings confirmed a significant correlation between the residual and the level of belt looseness.

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Condition Evaluation for Railway Running Units Using Infra-red Thermography: Seok Jin Kwon, Min Soo Kim, Jung Won Seo, Young Sam Ham; J. Korean Soc. Precis. Eng. 2023;40(6):433-439.
Published online June 1, 2023; DOI: https://doi.org/10.7736/JKSPE.022.122

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Damage to the units related to driving and running of the railway vehicle may cause an inevitable accident due to defects and malfunctions in operation. In order to prevent such an accident, a non-destructive diagnostic technology that detects the damage is required. Previous researchers have researched and developed a monitoring system of the infrared thermography method to diagnose the condition of the railway vehicle driving and driving units. A system for monitoring running of the railway vehicle and temperature condition of the drive unit at a vehicle speed of 30 to 100 km/h was constructed, and a study on its applicability was conducted. In this study, a system for diagnosing an abnormal condition of the driving and running units while the vehicle is running with an infrared thermography diagnostic system was installed in the depot and operation route, and evaluation of the abnormal condition of the driving and running units was performed. The results show that the diagnosis system using infrared thermography can be used to identify abnormal conditions in the driving and running units of a railway vehicle. The diagnosis system can effectively inspect the normal and abnormal conditions in operation of a railway vehicle.

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Digital Thread for Machining Process: Hoon Hee Lee, Dong Yoon Lee; J. Korean Soc. Precis. Eng. 2023;40(5):373-381.
Published online May 1, 2023; DOI: https://doi.org/10.7736/JKSPE.023.034

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Currently digital transformation has a huge impact on human lives. Digital transformation does not just mean a transformation of a (non-) physical element to a digitally identifiable element. It focuses on the utilization of digital technology for transforming (improving) procedures or routines of business and operation. The manufacturing industry has been adopting the most recent digital technology, and lots of digital data are being created. To utilize the stored data, data analysis is essential. Because the manufacturing data is created in a different format at every manufacturing step, the integration of the data is always the bottleneck of the data analysis. Querying of the right data at the proper time is fundamental for high-level data analysis. The digital thread is introduced to provide the inter-reference of digital data based on a context. This paper proposes a digital thread framework for the machining process. The context of the proposed framework consists of the questions of how the product will be machined, how it is (was) being produced, and how it was made. A prototype software was developed to verify the proposed framework by implementing the creating, storing, and querying modules for simulation, monitoring, and inspection data.

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A Review of Intelligent Machining Process in CNC Machine Tool Systems
Joo Sung Yoon, Il-ha Park, Dong Yoon Lee
International Journal of Precision Engineering and Manufacturing.2025; 26(9): 2243. CrossRef

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Process Monitoring and Part Program Optimization Using Virtual Machine Tools: Chang-Ju Kim, Segon Heo, Chan-Young Lee, Jung Seok Oh; J. Korean Soc. Precis. Eng. 2022;39(12):879-884.
Published online December 1, 2022; DOI: https://doi.org/10.7736/JKSPE.022.118

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A virtual machine tool, a computer simulation model of the machine motion and cutting process with a level of accuracy and consistency that can replace an accurate machine tool, is one of the critical digital transformation technologies in the manufacturing industry. During the machine development phase, cost and time can be reduced by evaluating machining efficiency and quality through virtual prototyping. In the machine application phase, virtual machine tools can be used to accurately assess the condition of equipment and processes by analyzing actual data combined with simulated data. This paper introduces a virtual machine tool system that can analyze the behavior of an accurate machine tool by integrating physical models of structure, numerical controller, and cutting process. The key features of the virtual machine tool, synchronous machining simulation, machining stability detection, machining error estimation, and part program optimization, were evaluated through various machining tests with a vertical 3-axis milling machine.

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A Review of Intelligent Machining Process in CNC Machine Tool Systems
Joo Sung Yoon, Il-ha Park, Dong Yoon Lee
International Journal of Precision Engineering and Manufacturing.2025; 26(9): 2243. CrossRef

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Tool Wear Monitoring System based on Real-Time Cutting Coefficient Identification: Young Jae Choi, Ki Hyeong Song, Jae Hyeok Kim, and Gu Seon; J. Korean Soc. Precis. Eng. 2022;39(12):891-898.
Published online December 1, 2022; DOI: https://doi.org/10.7736/JKSPE.022.111

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Among the monitoring technologies in the metal-cutting process, tool wear is the most critical monitoring factor in real machining sites. Extensive studies have been conducted to monitor equipment breakdown in real-time. For example, tool wear prediction studies using cutting force signals and deducting force coefficient values from the cutting process. However, due to many limitations, those wearable monitoring technologies have not been directly adopted in the field. This paper proposes a novel tool wear predictor using the cutting force coefficient with various cutting tools, and its validity evaluates through cutting tests. Tool wear prediction from the cutting force coefficient should conduct in real-time for adoption in real machining sites. Therefore, a real-time calculation algorithm of the cutting force coefficient and a tool wear estimation method proposes, and they compare with actual tool wear in cutting experiments for validation. Validation cutting tests are conducted with carbon steel and titanium, the most commonly used materials in real cutting sites. In future work, validation will be conducted with different materials and cutting tools, considering the application in real machining sites.

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Citations to this article as recorded by

A Review of Intelligent Machining Process in CNC Machine Tool Systems
Joo Sung Yoon, Il-ha Park, Dong Yoon Lee
International Journal of Precision Engineering and Manufacturing.2025; 26(9): 2243. CrossRef

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A State-of-the-Art Review of Structural Monitoring Using Piezoelectric Paint Sensors: Hyunjin Bae, Kyungwho Choi; J. Korean Soc. Precis. Eng. 2021;38(12):927-934.
Published online December 1, 2021; DOI: https://doi.org/10.7736/JKSPE.021.092

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Recently, large-scale accidents caused by minor damage from fatigue failure and impact on structures have been frequently reported. Therefore, a real-time damage monitoring system of structures is considered to be one of the most important technologies to ensure safety in various types of research. The piezoelectric sensor, which has an advantage of converting deformation of a structure into an electrical signal without using an additional power source, has been reported as one of the most suitable methods for real-time monitoring systems. This review aims to describe the structural monitoring system utilizing piezoelectric paint sensors. First, we present the concept of a piezoelectric paint sensor with the advantages of flexibility and piezoelectric performance. Then, factors affecting the performance of the piezoelectric paint sensor are introduced. Finally, an overview of piezoelectric paint sensors for structural monitoring, such as vibration detection and impact monitoring, are provided. The state-of-the-art of the application of the piezoelectric sensor is also introduced, providing feasibility in industrial fields.

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Evaluation of MWCNT/PU sponge-based triboelectric nanogenerator for harvesting mechanical energy
Insik Jo, Byungchul Kim, Hyungsik Won, SunHee Kim, Kyungwho Choi, Dukhyun Choi
Functional Composites and Structures.2025; 7(3): 035010. CrossRef

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Development of Moving Mirror Assembly in the Spectroscopic Sensor for Remote Gas Monitoring: Hyo-Wook Bae, Hankee Jang, Do-Hyun Park, Ho-Sang Kim; J. Korean Soc. Precis. Eng. 2021;38(8):581-587.
Published online August 1, 2021; DOI: https://doi.org/10.7736/JKSPE.021.025

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Spectroscopic sensors have been used in the field of optics and chemical analysis, and the need for remote gas monitoring in a portable form has increased. Hence, it is essential to design, manufacture, and develop a moving mirror, which that can generate the optical path difference for spectroscopic sensor. It is important to verify whether it can satisfy design requirements for the actual spectroscopic interferometer application by evaluating its performance. In this paper, a moving mirror assembly with high-speed transfer capability for a portable spectroscopic sensor is fabricated and tested. For application to a portable spectrometer, design requirements, such as moving distance, speed, and stiffness, are set and the mechanical structure, including the voice coil motor and elastic guide, satisfying these requirements is proposed. Through finite element analysis, performance of the proposed moving mirror assembly is predicted. By testing the performance after fabrication, it is verified that the proposed mirror is capable of linear movement with travel distance of several millimeters and moving speed of tens of Hz. Optical testing result shows that the proposed moving mirror can generate linear motion with a tilting error below 10 arcsecond and can be applied to the actual spectroscopic interferometer in future.

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Simulation Study on Line-of-sight Stabilization Controller Design for Portable Optical Systems
Jae Woo Jung, Sang Won Jung, Jae Hyun Kim, Seonbin Lim, Youngjin Park, Onemook Kim, Jaehyun Lim, Jae Ho Jin, No-Cheol Park, Jun Young Yoon
Journal of the Korean Society for Precision Engineering.2025; 42(2): 175. CrossRef
Power Consumption Analysis and Optimal Operation Method of Wireless Multi-sensor Module
Hyun Sik Son, Duck-Keun Kim, Kwang Eun Ko, Seung-Hwan Yang
Journal of the Korean Society for Precision Engineering.2025; 42(10): 843. CrossRef
Structural Design of Fast Steering Mirror with Reluctance Actuator
Onemook Kim, Seonbin Lim, Jaewoo Jung, Sangwon Jung, Jaehyun Kim, Bomin Kang, Junyoung Yoon, Seounghan Lee, Byoungju Lee, Yonghoon Lee, Hyeongrae Kim, No-cheol Park
Transactions of the Korean Society for Noise and Vibration Engineering.2024; 34(3): 330. CrossRef
Design optimization of a flexure spring used in small-sized ultra-precise optical instrument
Jin Kim, Dong-Chan Lee, Ho-Sang Kim
Heliyon.2023; 9(12): e22560. CrossRef
Development of piezoelectric fast steering mirror with tilt error compensation for portable spectroscopic sensor
Ho-Sang Kim, Kyoung Don Lee, Chan-Hee Lee, Won-Gi Lee
Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture.2023; 237(12): 1847. CrossRef

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A Study on Cutting Quality Using a Mahalanobis Distance: Bo-Ram Lee, Tae-Jong Yun, Won-Bin Oh, Chung-Woo Lee, Hak-Hyoung Kim, Yeong-Jae Jeong, Ill-Soo Kim; J. Korean Soc. Precis. Eng. 2021;38(4):253-260.
Published online April 1, 2021; DOI: https://doi.org/10.7736/JKSPE.020.070

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Social interest in the 4th industry, intelligent factories, and smart manufacturing is continually growing along with the core technologies like big data and artificial intelligence, which can generate meaningful information by collecting and accumulating sensor data. Demand for industrial automation equipment is increasing worldwide due to the efforts needed to modernize manufacturing facilities, reduce automation and cycle time, and improve quality. Currently, the majority of research is focused on the development of automation facilities and improving productivity. The research on the contents of real-time data considering the characteristics of the cutting machine plasma machine is insufficient. In this study, based on the current data measured according to cutting current and cutting speed, a reference value for cutting quality is presented and the optimal process parameter has been selected. A model for predicting cutting quality by introducing the Mahalanobis Distance Method is presented. An attempt has been made to derive selection and optimal cutting process variables. Based on the predictive model, threshold values were specified and used in real-time data to consider the correlations between multivariate variables and evaluate the degree of scattering around the average of specific values of each variable. Also, process parameters suitable for surface roughness were calculated.

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A quantitative diagnostic method of feature coordination for machine learning model with massive data from rotary machine
Yoonjae Lee, Byeonghui Park, Minho Jo, Jongsu Lee, Changwoo Lee
Expert Systems with Applications.2023; 214: 119117. CrossRef
Silicon nanoparticles: fabrication, characterization, application and perspectives
Taeyeong Kim, Jungchul Lee
Micro and Nano Systems Letters.2023;[Epub] CrossRef
Feature selection algorithm based on density and distance for fault diagnosis applied to a roll-to-roll manufacturing system
Hyogeun Oh, Yoonjae Lee, Jongsu Lee, Changbeom Joo, Changwoo Lee
Journal of Computational Design and Engineering.2022; 9(2): 805. CrossRef
Impact of Sensor Data Characterization with Directional Nature of Fault and Statistical Feature Combination for Defect Detection on Roll-to-Roll Printed Electronics
Yoonjae Lee, Minho Jo, Gyoujin Cho, Changbeom Joo, Changwoo Lee
Sensors.2021; 21(24): 8454. CrossRef

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Cutting Force Estimation Using Feed Motor Drive Current in Cutting Process Monitoring: Ki Hyeong Song, Dong Yoon Lee, Kyung Hee Park, Jae Hyeok Kim, Young Jae Choi; J. Korean Soc. Precis. Eng. 2020;37(11):803-812.
Published online November 1, 2020; DOI: https://doi.org/10.7736/JKSPE.020.094

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The cutting force signal has traditionally served as a reference in conducting the monitoring studies using a variety of sensors to identify the cutting phenomena. There have been continuing studies on how to monitor the cutting force indirectly. It is because it is easier to access when considering an application to the actual machining site. This paper discusses a method of indirectly monitoring the cutting force using the feed drive current to analyze the change in the trend of the cutting force over the lapse of machining time. This enables the analysis of the cutting force by separating it in the X and Y axes of the machining plane. To increase the discrimination of the signal related to the actual cutting phenomenon from the feed drive current signal, a bandpass filter was applied based on the tooth passing frequency. The relationship between the feed drive current and the cutting force analyzed from the machining signal of actual machining conditions was applied to convert the feed drive current into the cutting force. It has been verified through experiments that the cutting load can be estimated with markedly high accuracy as a physical quantity of force from the feed motor current.

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Tool Wear Monitoring System based on Real-Time Cutting Coefficient Identification
Young Jae Choi, Ki Hyeong Song, Jae Hyeok Kim, Gu Seon Kang
Journal of the Korean Society for Precision Engineering.2022; 39(12): 891. CrossRef

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Comparative Analysis and Monitoring of Tool Wear in Carbon Fiber Reinforced Plastics Drilling: Kyeong Bin Kim, Jang Hoon Seo, Tae-Gon Kim, Martin Byung-Guk Jun, Young Hun Jeong; J. Korean Soc. Precis. Eng. 2020;37(11):813-818.
Published online November 1, 2020; DOI: https://doi.org/10.7736/JKSPE.020.091

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Recently, carbon fiber-reinforced plastic (CFRP) has been attracting much attention in various industries because of its beneficial properties such as excellent strength, modulus per unit density, and anti-corrosion properties. However, there are several issues in its application to various fields. Severe tool wear issues in its machining have been noted as one of the most serious problems because it induces various serious machining failures such as delamination and splintering. In this regard, timely tool replacement is essential for reducing the influence of tool wear. In this study, tool wear, especially flank wear, in the CFRP drilling was investigated and monitored. First, the reproducibility of tool wear under the same machining condition was experimentally evaluated. And it is demonstrated that tool wear may remarkably differ even though the same machining condition is applied to the tools. Then, tool wear monitoring based on the feed motor torque was applied to the detection of tool life ending in the CFRP drilling process. Consequently, it was demonstrated that the average and maximum detection error of the tool life end were less than 7 and 14%, respectively.

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Experimental research on multi-structural parameter optimization of rhombic tooth endmill based on DOE in CFRP milling
Xiaochen Zuo, Junxue Ren, Tiejun Song, Tao Zeng, Mengliu Zhang, Hexuan Liu
Journal of Materials Research and Technology.2025; 38: 2892. CrossRef
Laser Drilling of Micro-Hole Array on CFRP Using Nanosecond Pulsed Fiber Laser
Do Kwan Chung
Journal of the Korean Society of Manufacturing Process Engineers.2024; 23(5): 92. CrossRef
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Do Kwan Chung, Chan Ho Han, Yu Jin Choi, Jun Seo Park
Journal of the Korean Society for Precision Engineering.2023; 40(2): 99. CrossRef
Comparison of TiAlN DLC and PCD Tool Wear in CFRP Drilling
Jong-Hyun Baek, Su-Jin Kim
Journal of the Korean Society of Manufacturing Process Engineers.2022; 21(5): 77. CrossRef