• Transactions of Materials Processing
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• v.31 no.2
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• pp.103-108
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• 2022

Systematic quality control based on real time data is required for modern factories. This study introduced a method of predicting punch wear in the trimming process of automobile parts. Based on monitoring data of the mass production process using a bolt-type piezo sensor, it was shown that precursor symptoms of die wear could be predicted from the change in load pattern with respect to production volume. The load pattern that changed according to the wear of the die was verified by numerical analysis.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.5
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• pp.891-897
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• 2009

This paper presents a novel load management technique that can lower the peak demand caused by package airconditioner loads in large apartment complex. An intelligent hierarchical load management system composed of a Central Intelligent Management System(CIMS) and multiple Local Intelligent Management Systems(LIMS) is proposed to implement the proposed technique. Once the required amount of the power reduction is set, CIMS issues tokens, which can be used by each LIMS as a right to turn on the airconditioner. CIMS creates and maintains a queue for fair and proper allocation of the tokens among the LIMS requesting tokens. By adjusting the number tokens and queue management policies, desired power reduction can be achieved smoothly. The Markov Birth and Death process and the Balance Equations utilizing the Diffusion Model are employed for evaluation of queue performances during transient periods until the static balances among the states are achieved. The proposed technique is tested using a summer load data of a large apartment complex and give promising results demonstrating the usability in load management while minimizing the customer inconveniences.

• Journal of Korea Game Society
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• v.17 no.5
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• pp.103-112
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• 2017

In recent years, expansions and advances of the Internet of Things (IoTs) in a distributed MMOGs (massively multiplayer online games) architecture have resulted in massive growth of data in terms of server workloads. We propose a combing Sparse Autoencoder and one of platforms in MMOGs, ProGReGA. In the process of Sparse Autoencoder, data representation with respect to enhancing the feature is excluded from this set of data. In the process of load balance, the graceful degradation of ProGReGA can exploit the most relevant and less redundant feature of the data representation. We find out that the proposed algorithm have become more stable.

• Journal of Industrial Technology
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• v.18
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• pp.173-180
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• 1998

A high speed and stable A/D conversion data process is required to weigh a mass on moving conveyer weighing platter. The paper presents a new method to obtain stable and fast automatic weighing A/D conversion data process. Dynamic weighting system which is constructed with dual load cell is realized by the stable A/D conversion data process algorithm using DSP. The proposed method is applied to the real design, and that experimental results showed good performances of the weighing stability.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.173-180
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• 2023

Smart factory companies are installing various sensors in production facilities and collecting field data. However, there are relatively few companies that actively utilize collected data, academic research using field data is actively underway. This study seeks to develop a model that detects anomalies in the process by analyzing spindle power data from a company that processes shafts used in automobile throttle valves. Since the data collected during machining processing is time series data, the model was developed through unsupervised learning by applying the Holt Winters technique and various deep learning algorithms such as RNN, LSTM, GRU, BiRNN, BiLSTM, and BiGRU. To evaluate each model, the difference between predicted and actual values was compared using MSE and RMSE. The BiLSTM model showed the optimal results based on RMSE. In order to diagnose abnormalities in the developed model, the critical point was set using statistical techniques in consultation with experts in the field and verified. By collecting and preprocessing real-world data and developing a model, this study serves as a case study of utilizing time-series data in small and medium-sized enterprises.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.1
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• pp.147-152
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• 2005

The exhaust system of automobile is faced with random or spectrum types of fatigue loads during usage life and so needs to be closely estimated for quality and performance to have enough certainty on design endurance lift during preliminary design process. Structural operation conditions, operation load history, property of material and manufacturing process etc. should be considered by performing experiment approach. Using the software program for predicting fatigue life quickly and exactly in preliminary design stage saves plenty of time and cost generated by fatigue tests. In this paper, fatigue life prediction was performed on the basis of fatigue analysis using MSC/FATIGUE and load data from field test and the life of development items was estimated and compared through the results.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.6
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• pp.64-69
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• 2016

Vehicle clutch measurement for disc cushion variation was developed for the production of high quality Dual clutch transmissions. The developed device is composed of load cells for load measurement and LVDT for measuring the distance variation measurement in cushion variation. The servo motor-driven electric press for flexible loads that was developed was controlled by a PC-based HMI system, LabVIEW, and the device was able to continuously record real time measurement data with the accuracies of ${\pm}0.1\;kgf$ load and ${\pm}5{\mu}m$ cushion amount, which is far above the requirements of commercial vehicle standards.

• KIISE Transactions on Computing Practices
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• v.22 no.1
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• pp.44-49
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• 2016

Recently, data has been growing dramatically along with the growth of social media and digital devices. A distributed memory processing system has been used to efficiently process large amounts of data. However, if a load is concentrated in a certain node in distributed environments, a node performance significantly degrades. In this paper, we propose a load balancing scheme to distribute load in a distributed memory environment. The proposed scheme replicates hot data to multiple nodes for managing a node's load and migrates the data by considering the load of the nodes when nodes are added or removed. The client reduces the number of accesses to the central server by directly accessing the data node through the metadata information of the hot data. In order to show the superiority of the proposed scheme, we compare it with the existing load balancing scheme through performance evaluation.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.2
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• pp.45-52
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• 2002

Load modeling is classified into two methods according to approaching method, so called the measurement and component-based method. The measurement method is to model the load characteristics measured directly at substations and feeders. But it is difficult to measure continuously load characteristics from naturally occurring. system variation. The component-based method consists of the fellowing process; component load modeling, composition rate estimation and aggregation of component loads, etc. In this paper, the characteristic experiment of component loads was performed to obtain data for the component load modeling as the component-based method. At first, representative component loads were selected by the proposed method considering the accuracy of load modeling and the performance possibility of component load experiment in the laboratory. Also an algorithm was Proposed to identify the reliability of data obtained from the component load characteristic experiments. In addition, the results were presented as the case studies.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.419-421
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• 2002

This paper presents a methodology for the application of Unified Modeling Language (UML) to develop the new load management system. Development of new load management system in competitive electricity market is very complex since it requires too much data of power system. For the efficient and flexible design to develop of new load management system, a UML approach in applied which is composed of a class diagram, package diagram using Rational Rose Unified Process.