• The Journal of Bigdata
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• v.8 no.2
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• pp.149-163
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• 2023

Due to the continuous growth of the E-commerce market, the volume of orders that fulfillment centers have to process has increased, and various customer requirements have increased the complexity of order processing. Along with this trend, the operational efficiency of fulfillment centers due to increased labor costs is becoming more important from a corporate management perspective. Using historical performance data as training data, this study focused on real-time box recommendations applicable to packaging areas during fulfillment center shipping. Four types of data, such as product information, order information, packaging information, and delivery information, were applied to the machine learning model through pre-processing and feature-engineering processes. As an input vector, three characteristics were used as product specification information: width, length, and height, the characteristics of the input vector were extracted through a feature engineering process that converts product information from real numbers to an integer system for each section. As a result of comparing the performance of each model, it was confirmed that when the Gradient Boosting model was applied, the prediction was performed with the highest accuracy at 95.2% when the product specification information was converted into integers in 21 sections. This study proposes a machine learning model as a way to reduce the increase in costs and inefficiency of box packaging time caused by incorrect box selection in the fulfillment center, and also proposes a feature engineering method to effectively extract the characteristics of product specification information.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.3
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• pp.56-62
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• 2022

The tank engine clutch flange constitutes a tank on which the engine and transmission of the tank are mounted. The engine clutch flange is fabricated using a difficult-to-cut material that exhibits high strength and hardness. It is difficult to process and requires considerable processing expertise. In addition, the engine clutch flange for the tank requires high machining precision because it is a system in which the connection is detachable. Because it requires high processing precision, the measurement of products equally important as processing. However, productivity is low owing to the significant amount of time required to measure each product using a three-dimensional coordinate measuring machine. Hence, this study is conducted to improve the productivity of the female tank engine clutch flange. Dedicated hobs and jigs are designed and manufactured to convert the existing end-mill cutting processing into hobbing cutting processing. An engine clutch for the tanks is manufactured using the manufactured dedicated hob and jig, and the shortening time is verified by measuring the processing time. In addition, a jig for inspection is designed and manufactured to measure the precision of the product. To verify the inspected product, the product precision is measured using a contact-type three-dimensional coordinate measuring machine and a surface roughness measuring instrument. The study confirmed that the productivity of the engine clutch flange product for tanks can be improved by simplifying the process, reducing the processing time, and simplifying product inspection.

• Journal of Korean Society for Quality Management
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• v.51 no.1
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• pp.55-65
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• 2023

Purpose: The purpose of this study is to propose an optimization process to improve product yield in the process using process data. Recently, research for low-cost and high-efficiency production in the manufacturing process using machine learning or deep learning has continued. Therefore, this study derives major variables that affect product defects in the manufacturing process using eXplainable Artificial Intelligence(XAI) method. After that, the optimal range of the variables is presented to propose a methodology for improving product yield. Methods: This study is conducted using the injection molding machine AI dataset released on the Korea AI Manufacturing Platform(KAMP) organized by KAIST. Using the XAI-based SHAP method, major variables affecting product defects are extracted from each process data. XGBoost and LightGBM were used as learning algorithms, 5-6 variables are extracted as the main process variables for the injection process. Subsequently, the optimal control range of each process variable is presented using the ICE method. Finally, the product yield improvement methodology of this study is proposed through a validation process using Test Data. Results: The results of this study are as follows. In the injection process data, it was confirmed that XGBoost had an improvement defect rate of 0.21% and LightGBM had an improvement defect rate of 0.29%, which were improved by 0.79%p and 0.71%p, respectively, compared to the existing defect rate of 1.00%. Conclusion: This study is a case study. A research methodology was proposed in the injection process, and it was confirmed that the product yield was improved through verification.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.4
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• pp.23-29
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• 2016

Rotary machine is major equipment in industry. The rotary machine is applied for a machine tool, ship, vehicle, power plant, and so on. But a spindle fault increase product's expense and decrease quality of a workpiece in machine tool. A turbine in power plant is directly connected to human safety. National crisis could be happened by stopping of rotary machine in nuclear plant. Therefore, it is very important to know rotary machine condition in industry field. This study mentioned fault diagnosis algorithm with statistical parameter and empirical mode decomposition. Vibration locations can be found by analyze kurtosis of data from triaxial axis. Support vector of data determine threshold using hyperplane with fault location. Empirical mode decomposition is used to find fault caused by intrinsic mode. This paper suggested algorithm to find direction and causes from generated fault.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.2_2
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• pp.415-424
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• 2024

This study analyzes trends and characteristics of the machine tool remanufacturing industry and proposes a standard process that considers environmental impact assessment during the remanufacturing process. First, trends in remanufacturing and environmental regulations are reviewed. And the current status of the machine tool remanufacturing industry and cases of national R&D projects related to machine tools are analyzed. Machine tool remanufacturing has a high resource saving effect, and remanufacturing is carried out as a finished product rather than as a part. And the scope of remanufacturing work is very wide due to the performance improvement of the machine and the addition of features. In order for the machine tool remanufacturing industry to be competitive, it is necessary to create products with high added value. In addition, in order to respond to international environmental regulations, it is necessary to secure related data by conducting an environmental impact assessment together during remanufacturing.

• Proceedings of the KAIS Fall Conference
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• 2001.11a
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• pp.107-110
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• 2001

Design process is the essential technology for development of industry in nation, but contrary to its significance the trial for development of design technology is not so active because it requires a lot of time and efforts to educate design engineers. For that reason, most of enterprises concentrated their efforts for improving product technologies to get instant effects in short periods, and through these trials considerable results could be achieved. Recently, however, many people realized that industrial development through only product technology without design technology has limits, accordingly, a lot of efforts, to educate machine designers whom have enough knowledge and ability on design through advanced design technology, concentrated for industrial development. In general, the curriculum of conventional education for machine design in most universities is mainly compose of three subjects, the theory for elements design, geometric modeling practice for mating engineering drawings using CAD software, and analysis of elements using CAE software fur determining whether proposed solution is correct or rational. Furthermore, because these three subject are provided for students as the completely separated subjects, most of students who have educated with this method have no enough ability to Integrate all design process into a comprehensive whole process. This paper proposes a new design education methodology through reverse engineering that can overcome these problems of conventional education method.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.11
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• pp.63-68
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• 2019

The dimensional quality of flexible foams is often difficult to be evaluated through general machine vision inspection methods due to the free deformation of the outer shape. For the evaluation of the dimensions of flexible foams, methods of estimating the size of the product through the expansion rate of the product surface are evaluated. Specimens with various dimensions and surface gratings are prepared, and the degree of surface expansion is measured through machine vision. The correlation, between the measured surface grid size and the actual size of test specimens, is analyzed. We further analyze the correlation between the size of test specimens and the position of the surface grid. This study provides a basis for estimating the actual dimensions of specimens by measuring the surface expansion of flexible foams.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.134-134
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• 2021

Precipitation is a crucial component of water cycle and play a key role in hydrological processes. Traditionally, gauge-based precipitation is the main method to achieve high accuracy of rainfall estimation, but its distribution is sparsely in mountainous areas. Recently, satellite-based precipitation products (SPPs) provide grid-based precipitation with spatio-temporal variability, but SPPs contain a lot of uncertainty in estimated precipitation, and the spatial resolution quite coarse. To overcome these limitations, this study aims to generate new grid-based daily precipitation using Automatic weather system (AWS) in Korea and multiple SPPs(i.e. CHIRPSv2, CMORPH, GSMaP, TRMMv7) during the period of 2003-2017. And this study used a machine learning based Random Forest (RF) model for generating new merging precipitation. In addition, several statistical linear merging methods are used to compare with the results of the RF model. In order to investigate the efficiency of RF, observed data from 64 observed Automated Synoptic Observation System (ASOS) were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the random forest model showed higher accuracy than each satellite rainfall product and spatio-temporal variability was better reflected than other statistical merging methods. Therefore, a random forest-based ensemble satellite precipitation product can be efficiently used for hydrological simulations in ungauged basins such as the Mekong River.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1994.10a
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• pp.107-117
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• 1994

A design methodology is applied for manufacturing a disk-brake piston component and a washing machine container. The design criteria are the limit drawing ratio and the forging load within the available press limit. Also, the final product should not have any geometrical defect. The rigid-plastic and elastic-plastic FEM have been applied to simulate both of the conventional manufacturing processes, respectively, which include deep drawing and forging process. Simulations of one stage process from a selected stock to the final product shape are performed for generating information on additional requirements for metal flow. The best manufacturing processes are selected, which is using a hemispherical punch in the deep drawing process for both disk-brake piston component and washing machine container.

• Journal of the military operations research society of Korea
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• v.24 no.2
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• pp.162-169
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• 1998

This study presents an single machine scheduling algorithm minimize lateness of product by controlling machining speed. Generally, production scheduling uses the information of process planning. But the production scheduling algorithm has not considered the control of machining speed in its procedures. Therefore, the purpose of this study is to consider the machining speed in production scheduling algorithm for efficient production scheduling. Machining time and machining cost required to manufacture a piece of a product are expressed as a unimodal convex function with respect to machining speed, so it has minimal point at minimum time speed or the minimum cost speed. Therefore, because of considering the machining cost, the control of machining speed for the algorithm is executed between minimum speed and maximum speed. An example is demonstrated to explain the algorithm.