International Journal of Precision Engineering and Manufacturing-Smart Technology

Regular Paper

January 1, 2023

Sound Recognition based on Convolutional Neural Network for Real-Time Cutting State Monitoring of Tube Cutting Machine

Eunseob Kim, Huitaek Yun, Otavio C. Araujo, Martin B. G. Jun

Int. J. Precis. Eng. Manuf.-Smart Tech.. 2023;1(1):1-18.

Machine sound monitoring is widely used in various applications of operational state and diagnostic monitoring as machine-emitted sound contains the operational and process information. In the metal cutting industry, it...

Regular Paper

January 1, 2023

Prediction of Spread in Steel Wire Rod Rolling: Transferable and Explainable Approach

Soheil Amani, Jong Bin Lee, Simon S. Park

Int. J. Precis. Eng. Manuf.-Smart Tech.. 2023;1(1):19-33.

Spread is a major parameter in the steel wire rod rolling process since it is required for the calculation of material cross-sectional area and other rolling characteristics. Therefore, it is...

Regular Paper

January 1, 2023

Artificial Intelligence (AI)–Based Surface Quality Prediction Model for Carbon Fiber Reinforced Plastics (CFRP) Milling Process

Jin Woo Kim, Jungsoo Nam, Geun Young Kim, Sang Won Lee

Int. J. Precis. Eng. Manuf.-Smart Tech.. 2023;1(1):35-47.

The objective of this study is to develop a surface quality prediction model for CFRP milling based on artificial intelligence and enhance the model performance by proposing a novel feature...

Regular Paper

January 1, 2023

A Rapid Learning Model based on Selected Frequency Range Spectral Subtraction for the Data-Driven Fault Diagnosis of Manufacturing Systems

Seungyon Cho, Hea-Ryeon Seo, Geonhwi Lee, Seung-Kyum Choi, Hae-Jin Choi

Int. J. Precis. Eng. Manuf.-Smart Tech.. 2023;1(1):49-62.

Limited amount of training dataset is often a critical problem in developing a diagnosis model or computational intelligence of mechanical failures. In this paper, we propose a Selected Frequency Range...

Regular Paper

October 8, 2022

OPC UA-Based Machining Cell Monitoring System for Multi-Vendors’ Machine Tools and Industrial Robots

Joo-Sung Yoon, Yeong-Deuk Kim, Jaehak Lee, Dong Yoon Lee

Int. J. Precis. Eng. Manuf.-Smart Tech.. 2023;1(1):63-69.

Monitoring systems for the manufacturing field are essential. These systems have various architectures and scales to meet more diverse requirements depending on their purpose. However, communication is commonly fundamental for...

Regular Paper

January 1, 2023

Surface Assessment of Transparent Glass Plate with Wavelength-Modulated Interferometry and Harmonic Phase-Iterative Method

Sungtae Kim, Yangjin Kim, Naohiko Sugita, Mamoru Mitsuishi

Int. J. Precis. Eng. Manuf.-Smart Tech.. 2023;1(1):71-81.

Multiple reflections and nonlinearity of phase modulating need to be compensated to accurately profile the surface of the glass plate using wavelength-modulated interferometry. In this study, to assess the glass...

Regular Paper

January 1, 2023

Machine Learning Interatomic Potential to Investigate Fundamentals of Electrolytes for Li-ion Solid-State Batteries

Kyoungmin Min

Int. J. Precis. Eng. Manuf.-Smart Tech.. 2023;1(1):83-91.

Machine learning and deep learning are used to construct interatomic potential with superior performance by satisfying the accuracy of density functional theory (DFT) calculations while requiring computational resources comparable to...

Review

January 1, 2023

Key Enabling Technologies for Smart Factory in Automotive Industry: Status and Applications

Jongsuk Lee, Ping Chong Chua, Lequn Chen, Poh Huat Nicholas Ng, Yerim Kim, Qiong Wu, Sumin Jeon, Jihwan Jung, Siheon Chang, Seung Ki Moon

Int. J. Precis. Eng. Manuf.-Smart Tech.. 2023;1(1):93-105.

In line with the unpredictable variety of demands and acceleration into the electric vehicle era, automakers have efforted on smart factories utilizing new manufacturing platforms with a cellular manufacturing system...

Industry Case Study

January 1, 2023

Cyber-Physical Systems Framework for Predictive Metrology in Semiconductor Manufacturing Process

Jay Lee, Huwei Dong, Dai-Yan Ji, Pradeep Kundu

Int. J. Precis. Eng. Manuf.-Smart Tech.. 2023;1(1):107-113.

The process of semiconductor manufacturing is very complex, and the downtime caused by equipment degradation at any process stage reduces yield and production efficiency. Thus, semiconductor machines’ maintenance and calibration...

MOST READ

A Rapid Learning Model based on Selected Frequency Range Spectral Subtraction for the Data-Driven Fault Diagnosis of Manufacturing Systems

Seungyon Cho (Cho S), Hea-Ryeon Seo (Seo HR), Geonhwi Lee (Lee G), Seung-Kyum Choi (Choi SK), Hae-Jin Choi (Choi HJ)

Sound Recognition based on Convolutional Neural Network for Real-Time Cutting State Monitoring of Tube Cutting Machine

Eunseob Kim (Kim E), Huitaek Yun (Yun H), Otavio C. Araujo (Araujo OC), Martin B. G. Jun (Jun MBG)

Current Issue: Volume 1(1); Jan 2023

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Current Issue

Volume 1(1); January

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Vol. 1
2023

No 1. Jan

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