• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.37
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• pp.63-70
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• 1996

This paper presents a model which may be used in optimal control of the Man-Machine systems in the aspect of information transmission. For this, we divided information into human parts and machine parts, and consider minimum error principle as a machine operating logic. Furthermore, we take the maximum information principle as a human information operating logic. This can be done in considering the Fisher Information and its transformed type, information inequality.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.34
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• pp.123-128
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• 1995

The grouping of parts into families and machines into cells poses an important problem in the design and planning of the flexible manufacturing system(FMS). This paper proposes a new optimal algorithm of forming machine-part groups to maximize the similarity, based on branching from seed machine and bounding on a completed part. This algorithm is illustrated with numerical example. This algorithm could be applied to the generalized machine-part grouping problem.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.4
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• pp.705-718
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• 1996

A similarity coefficient based algorithm is proposed to solve the machine cells and part families formation problem in group technology. Similarity coefficients are newly designed from the machine-part incidence matrix. Machine cells are formed using a recurrent neural network in which the similarity coefficients are used as connection weights between processing units. Then parts are assigned to complete the cell composition. The proposed algorithm is applied to 30 different kinds of problems appeared in the literature. The results are compared to those by the GRAFICS algorithm in terms of the grouping efficiency and efficacy.

• Journal of Korean Institute of Industrial Engineers
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• v.18 no.2
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• pp.123-130
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• 1992

The group formation problem of the machine and part in Flexible Manufacturing System (FMS) is a very important issue in planning stage of FMS. This paper discusses the problem of machine-part group formation. The purpose of the study is to develop a heuristic algorithm, which can handle more realistic machine-part group formation problem by considering manufacturing factors. A new similarity coeffecient has been developed to solve more realistic machine-part group formation problem. For the purpose of illustations, a numerical example is presented.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.2
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• pp.94-103
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• 2019

Self Organizing Map (SOM) is a neural network that is effective in classifying patterns that form the feature map by extracting characteristics of the input data. In this study, we propose an algorithm to determine the cell formation and the machine layout within the cell for the cell formation problem with operation sequence using the SOM. In the proposed algorithm, the output layer of the SOM is a one-dimensional structure, and the SOM is applied to the parts and the machine in two steps. The initial cell is formed when the formed clusters is grouped largely by the utilization of the machine within the cell. At this stage, machine cell are formed. The next step is to create a flow matrix of the all machine that calculates the frequency of consecutive forward movement for the machine. The machine layout order in each machine cell is determined based on this flow matrix so that the machine operation sequence is most reflected. The final step is to optimize the overall machine and parts to increase machine layout efficiency. As a result, the final cell is formed and the machine layout within the cell is determined. The proposed algorithm was tested on well-known cell formation problems with operation sequence shown in previous papers. The proposed algorithm has better performance than the other algorithms.

• Journal of Biosystems Engineering
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• v.43 no.3
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• pp.161-172
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• 2018

Purpose: During tillage operations, the selection of a working machine (tool) depends on the soil conditions as well as the type of tillage operation to be performed. The goal of this research was to ascertain the effects of varying working machine parameters of a compact disc harrow on tillage operations under various soil moisture content (SMC) conditions. Methods: The working machine parameters were the disc spacing and machine speed. The tillage parameters under investigation were the soil inversion ratio (SIR), tillage cutting depth (TCD), and soil clod breakage ratio (SCB). To determine the SIR, the areas of the white regions before and after tillage were obtained. The ratio of the difference of the areas of the white regions before and after tillage to the area of the white regions before tillage was considered as the SIR. The SCB was obtained as the ratio of the weight of soil clods after sieving with a mesh size of <0.02 m to the total weight of the soil clods before sieving. The soil TCD was measured using a tape measure at random points after the tillage operation. The resulting data were statistically analyzed in a one-way analysis of variance. Results: The highest soil inversion was achieved when the machine speed was 0.2 m/s with the disc spaced at 0.2 m in the 16.5% SMC. At a 0.4-m/s machine speed and 0.3-m disc spacing the highest soil breakage was achieved in the 26.5% SMC. The highest TCD was achieved at a 0.2-m/s machine speed and 0.2-m disc spacing in the 16.5% SMC. Conclusions: It was concluded that varying the working machine parameters, such as the disc spacing and machine speed, could significantly affect the soil inversion and soil clod breakage; however, it had no significant impact on the TCD.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.4
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• pp.23-32
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• 2009

• The Journal of Society for e-Business Studies
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• v.25 no.4
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• pp.143-154
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• 2020

With the increasing trend of making manufacturing system intelligent and autonomous, the introduction of robot-assist automation, like machine tending system for automated operation of CNC machine tools, is being actively carried out at many industrial sites. Most important part of this intelligent system to install machine tending system, is interface programming between the CNC machine tools and the industrial robot. Despite this importance, however, the machine tending system has many setup problems. it is necessary for difficult re-program of both controllers whenever a new CNC machine tool or robot is introduced. And, the helps of external engineers is required even though trivial changes due to the complex structure of the machine tending system. Authors of this paper introduces the integrated system of the interface between heterogeneous CNC machine tools and industrial robots. In addition, the digital twin implemented inside the machine tool controller enable shop-floor operators to change the interface programming easily. To implement this system, an integrated development environment for 1) an intelligent HMI platform that provide standardized interfaces to heterogeneous CNC machine tools and 2) a robot platform developing application software of various robots, was established. For easy un-tact environment, this paper explain the development of 3) a game-engine based web program of controlling and monitoring machine tending system remotely.

• Tribology and Lubricants
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• v.26 no.1
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• pp.52-55
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• 2010

This study investigates the friction of the roll stands in the high performance multi- holes slate fin machine which pin is using in heat transfer of radiator, oil cooler, inter cooler, condenser and evaporator. The roll stand part is very important to maintain the high performance fin machine. This multi-holes form roll type is the first time in our country so it will be helpful to increases the export and product of heat transfer. It was include the technical of form rolling system which was self development. Then it will be improve the electric home appliances, future motor vehicle device and industrial machine.

• Korean Journal of Agricultural Science
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• v.50 no.3
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• pp.373-382
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• 2023

The task of sorting and excluding blemished apples and others that lack commercial appeal is currently performed manually by human eye sorting, which not only causes musculoskeletal disorders in workers but also requires a significant amount of time and labor. In this study, an automated apple-sorting machine was developed to prevent musculoskeletal disorders in apple production workers and to streamline the process of sorting blemished and non-marketable apples from the better quality fruit. The apple-sorting machine is composed of an arm-rest, a main body, and a height-adjustable part, and uses object detection through a machine learning technology called 'You Only Look Once (YOLO)' to sort the apples. The machine was initially trained using apple image data, RoboFlow, and Google Colab, and the resulting images were analyzed using Jetson Nano. An algorithm was developed to link the Jetson Nano outputs and the conveyor belt to classify the analyzed apple images. This apple-sorting machine can immediately sort and exclude apples with surface defects, thereby reducing the time needed to sort the fruit and, accordingly, achieving cuts in labor costs. Furthermore, the apple-sorting machine can produce uniform quality sorting with a high level of accuracy compared with the subjective judgment of manual sorting by eye. This is expected to improve the productivity of apple growing operations and increase profitability.