• International Journal of Quality Innovation
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• v.1 no.1
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• pp.89-96
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• 2000

Evolutionary operation (EVOP) is a continuous improvement system which explores a region of process operating conditions by deliberately creating some systematic changes to the process variable levels without jeopardizing the product. It is aimed at securing a satisfactory operating condition in full-scale manufacturing processes, which is generally different from that obtained in laboratory or pilot plant experiments. Information on how to improve the process is generated from a simple experimental design. Traditional EVOP procedures are established on the assumption that the variance of the response variable should be small and stable in the region of the process operation. However, it is often the case that process noises have an influence on the stability of the process. This process instability is due to many factors such as raw materials, ambient temperature, and equipment wear. Therefore, process variables should be optimized continuously not only to meet the target value but also to keep the variance of the response variables as low as possible. We propose a scheme to achieve robust process improvement. As a process performance measure, we adopted the mean square error (MSE) of the replicate response values on a specific operating condition, and used the Kruskal-Wallis test to identify significant differences between the process operating conditions.

• Clean Technology
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• v.18 no.2
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• pp.155-161
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• 2012

The purpose of this study is to remove paraffin wax binder effectively from powder injection molded part using supercritical fluids in powder injection molding process. For a thin powder injection molded part about 1-2 mm thickness, paraffin wax binder can be removed rapidly without any defect by traditional supercritical extraction process which has fixed high temperature and pressure condition. But, for a thick powder injection molded part, there are limitations in removing paraffin wax binder by the fixed high process condition because crack occurs at the beginning step. Therefore, here we studied variable condition debinding process that starts with mild process condition at the beginning step and then increase the process conditions simultaneously at each step. To find out the initial process condition that has the highest extraction yield without any defect for each sample thickness, we investigated various supercritical debinding conditions using 1-4 mm thickness ceramic injection molded sample. By using the variable condition debinding process that starts with the initial process condition at the first step and then increasing process conditions simultaneously at each step (temperature from 333.15 to 343.15 K, pressure from 12 to 27 MPa, and $CO_2$ flow rate from 1.5 to 10 L/min), over 95% of paraffin wax binder was removed from the 4 mm thick (10 mm diameter) ceramic injection molded disk samples within 5 hours.

• Journal of Powder Materials
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• v.29 no.6
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• pp.459-467
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• 2022

Soft magnetic powder materials are used throughout industries such as motors and power converters. When manufacturing Fe-based soft magnetic composites, the size and shape of the soft magnetic powder and the microstructure in the powder are closely related to the magnetic properties. In this study, Fe-Si-Al-P alloy powders were manufactured using various manufacturing process parameter sets, and the process parameters of the vacuum induction melt gas atomization process were set as melt temperature, atomization gas pressure, and gas flow rate. Process variable data that records are converted into 6 types of data for each powder recovery section. Process variable data that recorded minute changes were converted into 6 types of data and used as input variables. As output variables, a total of 6 types were designated by measuring the particle size, flowability, apparent density, and sphericity of the manufactured powders according to the process variable conditions. The sensitivity of the input and output variables was analyzed through the Pearson correlation coefficient, and a total of 6 powder characteristics were analyzed by artificial neural network model. The prediction results were compared with the results through linear regression analysis and response surface methodology, respectively.

• Journal of Korean Society for Quality Management
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• v.52 no.1
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• pp.43-56
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• 2024

Purpose: The injection molding process, crucial for plastic shaping, encounters difficulties in sustaining product quality when replacing injection machines. Variations in machine types and outputs between different production lines or factories increase the risk of quality deterioration. In response, the study aims to develop a system that optimally adjusts conditions during the replacement of injection machines linked to molds. Methods: Utilizing a dataset of 12 injection process variables and 52 corresponding sensor variables, a predictive model is crafted using Decision Tree, Random Forest, and XGBoost. Model evaluation is conducted using an 80% training data and a 20% test data split. The dependent variable, classified into five characteristics based on temperature and pressure, guides the prediction model. Bayesian optimization, integrated into the selected model, determines optimal values for process variables during the replacement of injection machines. The iterative convergence of sensor prediction values to the optimum range is visually confirmed, aligning them with the target range. Experimental results validate the proposed approach. Results: Post-experiment analysis indicates the superiority of the XGBoost model across all five characteristics, achieving a combined high performance of 0.81 and a Mean Absolute Error (MAE) of 0.77. The study introduces a method for optimizing initial conditions in the injection process during machine replacement, utilizing Bayesian optimization. This streamlined approach reduces both time and costs, thereby enhancing process efficiency. Conclusion: This research contributes practical insights to the optimization literature, offering valuable guidance for industries seeking streamlined and cost-effective methods for machine replacement in injection molding.

• Journal of Korean Society for Quality Management
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• v.33 no.4
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• pp.117-122
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• 2005

Variable sampling rate(VSR) scheme varies the sampling rate for the current sample depending on the previous value of the control statistic. In this paper, we propose EWMA control charts with variable parameter(VP) scheme, which allows both the sample rate(the sample size or the sampling interval) and the weight to vary. We investigate the effectiveness of the VP scheme relative to the fixed parameter(FP) scheme and the VSR scheme in EWMA control charts. It is shown that using the VP scheme gives some improvements to the ability in detecting small and moderate shifts in the process normal mean.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.178-180
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• 2001

State estimation in power system is to estimate state variable value which minimizes the error from the real state measured by the gauge and connection state of the circuit breaker. In the past, it was difficult to determine measure function considering the correlation of the measured values. In this paper, an extended state estimation is proposed to process easily various kinds of estimation variable. The proposed algorithm is developed by expanding state variable concept based on many measured values and treating correlation between estimation variable and state variable, it is considered that the state variable satisfy some limitations named "Equality Limitation conditions".

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.8
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• pp.66-71
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• 2022

Metal additive manufacturing (AM) has revolutionized several manufacturing industries. AM can generate large-scale metal components and produce complex geometries close to net-shapes. WAAM is an AM technology that has garnered considerable interest among industries owing to its economics and relatively high deposition rates. However, the heat accumulation in the weld bead during deposition triggers distortion and residual stress. To address these problems, various methods of interpass pressure rolling systems have been suggested in recent research. In addition, combining the rolling and WAAM processes can mitigate residual stresses. The constant-pressure rolling of the interlayer also affect the microstructure. The coarse microstructure of the as-deposited sample was altered to finer equiaxed grains via these methods. However, the bead-shape accuracy of the interlayer constant-pressure method does not consider the heat accumulation in each layer. Therefore, this study develops an interpass variable pressure rolling system that considers the heat accumulation of each layer. The interpass variable pressure rolling system comprises deposition, detection, pressure, and transport units. Finally, verification tests are performed on the interpass variable-pressure rolling system (at 500 kg) with the WAAM process, and the obtained results are discussed.

• Journal of Korean Society for Quality Management
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• v.36 no.4
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• pp.77-86
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• 2008

Due to the rapid growth in automated testing and manufacturing systems, screening inspection becomes very attractive. In this paper, we investigate the effects of limited capacity on screening inspection using a surrogate variable. The model is developed under the assumption that the reprocessed and nonreprocessed items are produced by the same manufacturing process and therefore their quality characteristics are independently and identically distributed. Profit models are constructed which involve four price/cost components; selling price, cost incurred by imperfect quality, reprocessing and quality inspection costs. Methods of finding the optimal screening limits are presented, and a numerical example is given. Sensitivity analyses are also performed to study the effect of a process standard deviation on this model.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.763-766
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• 2000

Rapid Prototyping(RP) techniques have their unique characteristics according to the working principles: stair-stepped surface of parts due to layer-by-layer stackin, low build speed caused by line-by-line solidification to build one layer, and additional post processing to improve surface roughness, so it is required very high cost to introduce and to maintain RP apparatus. The objective of this study is to develop software for automatic generation of unit shape part (USP) for a new RP process, Variable Lamination Manufacturing using linear hotwire cutting technique and expandable polystyrene foam sheet as part material (VLM-S). In order to examine the applicability of the developed software to VLM-S, USP's of general three-dimensional shapes, such as an auto-shift lever knob and a pyramid shape were generated.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.4
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• pp.134-144
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• 2014

With the advent of lean-six sigma era, an extensive use of analytic tools such as control charts is required in the field of manufacturing. In relation to statistical quality control (SQC) or process control (SPC), the Korean standards have undergone a meaningful change. In this study, the theoretic backgrounds for evaluating the control limits in connection with the variable control charts are examined in view of better understanding the related constants and coefficients. This paper is intended to help the quality control practitioners understand the mathematical backgrounds by comparing related quality control constants and also to encourage them to make use of and to take the advantage of the variable control charts which are very useful for implementing the concept of lean-six sigma in many industrial sites.