• 품질경영학회지
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• 제52권2호
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• pp.185-199
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• 2024

Purpose: The improvement of yield and quality in product manufacturing is crucial from the perspective of process management. Controlling key variables within the process is essential for enhancing the quality of the produced items. In this study, we aim to identify key variables influencing product defects and facilitate quality enhancement in CNC machining process using SHAP(SHapley Additive exPlanations) Methods: Firstly, we conduct model training using boosting algorithm-based models such as AdaBoost, GBM, XGBoost, LightGBM, and CatBoost. The CNC machining process data is divided into training data and test data at a ratio 9:1 for model training and test experiments. Subsequently, we select a model with excellent Accuracy and F1-score performance and apply SHAP to extract variables influencing defects in the CNC machining process. Results: By comparing the performances of different models, the selected CatBoost model demonstrated an Accuracy of 97% and an F1-score of 95%. Using Shapley Value, we extract key variables that positively of negatively impact the dependent variable(good/defective product). We identify variables with relatively low importance, suggesting variables that should be prioritized for management. Conclusion: The extraction of key variables using SHAP provides explanatory power distinct from traditional machine learning techniques. This study holds significance in identifying key variables that should be prioritized for management in CNC machining process. It is expected to contribute to enhancing the production quality of the CNC machining process.

• 한국기계가공학회지
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• 제21권5호
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• pp.61-66
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• 2022

This study investigated the characteristics and relationship between surface roughness and vibration according to the cutting conditions in the slot milling of AL7075-T6. The spindle speed, feed, and depth of cut were selected as independent variables and the amplitude of acceleration and surface roughness as dependent variables. Feed affected the surface roughness. As the spindle speed increased, the amplitude of vibration increased in the direction perpendicular to the feed direction. In addition, the amplitude of vibration and surface roughness showed a negative correlation. Under a given feed, the surface roughness improved as the vibration increased.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.42-45
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• 2003

The purpose of this study is the development or the extensive Rapid Prototyping Technique. which can resolve the long-term manufacturing process, shrinkage and deformation occurring rapid prototyping technique. To begin with. the various specimens for tensile were manufactured on the basis of this modeling technology. Then, many kinds of the laminate pieces for the test were made by using the sheet metals lmm and 1.5mm thickness which is composed of the same ingredient. The tensile specimen were manufactured by changing the process variables, Such as electric current, pressure and resistance welding time for the Rapid Prototyping with metal sheet. And then by using the Taguchi method. The interrelation between the specimen and mechanical properties were determined and the system for the optimum process variable organized.

• 한국분말재료학회지
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• 제29권6호
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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.

• 한국기계가공학회지
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• 제17권2호
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• pp.160-167
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• 2018

The purpose of this study is to develop a process for forming a MPa ultra-high strength steel sheet to reduce weight and improve product strength. To do this, we performed the initial process design based on empirical formulas in a handbook and experience of skilled engineers, and researched the effects of major process variables on spring back by analyzing the forming analysis and experimental results. This paper suggests an optimal process design of the seat rail lower parts, using a MPa ultra-high strength steel sheet. This satisfies the dimensional accuracy and strength requirements for the product.

• Journal of Biosystems Engineering
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• 제38권1호
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• pp.33-40
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• 2013

Purpose: The goal of this study was to build an accurate digital factory that evaluates the performance of a factory using computer simulation. To achieve this goal, we evaluated the effect of worker-related variables on production in a simulation model using comparative analysis of two cases. Methods: The overall work process and worker-related variables were determined and used to build a simulation model. Siemens PLM Software's Plant Simulation was used to build a simulation model. Also, two simulation models were built, where the only difference was the use of the worker-related variable, and the total daily production analyzed and compared in terms of the individual process. Additionally, worker efficiency was evaluated based on worker analysis. Results: When the daily production of the two models were compared, a 0.16% error rate was observed for the model where the worker-related variables were applied and error rate was approximately 5.35% for the model where the worker-related variables were not applied. In addition, the production in the individual processes showed lower error rate in the model that included the worker-related variables than the model where the worker-related variables were not used. Also, among the total of 22 workers, only three workers satisfied the IFRS (International Financial Reporting Standards) suggested worker capacity rate (90%). Conclusions: In the daily total production and individual process production, the model that included the worker-related variables produced results that were closer to the real production values. This result indicates the importance of worker elements as input variables, in regards to building accurate simulation models. Also, as suggested in this study, the model that included the worker-related variables can be utilized to analyze in more detail actual production. The results from this study are expected to be utilized to improve the work process and worker efficiency.

• 소성∙가공
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• 제14권1호
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• pp.57-64
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• 2005

This study deals with the cold forging process design for shaft in the main part of automobile motors with rectangular deep groove. In forging process, the accuracy and die lift is very important because it have influence on reduction of the production cost and the increase of the production rate. Therefore, it is necessary to develop the manufacturing process of shaft by cold forging., process variables are the cropped face angle of billet and the eccentric load of punch. The former is derived from cropping test, the latter is occurred by clearance between container and preform. Also, grooved preform select the process variable for decrease in punch deflection. We investigate that a deflection of punch and a deformation of preform to every process variables. Through this investigation, we suggest the optimal preform and process design, expect to be improved the tool life in forging process.

• 한국생산제조학회지
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• 제21권4호
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• pp.593-600
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• 2012

Thixomolding of Mg-alloy is a semi-solid injection molding process utilizing thixotropic phenomenon. Using this process, higher strength, thinner wall section and tighter tolerance without porosity are obtained. It has been applied for production of near-net-shape magnesium component. To design optimal thixomolding process of Mg-alloy part, molding conditions such as slurry temperature, mold temperature and injection time should be determined properly. Selection of these parameters has been dependent upon engineers' experience and intuitiveness. In this paper, to improve mechanical properties of the thixomolded product, optimal selection of process variables such as injection velocity, barrel temperature and die temperature in the process has been studied through microstructural analysis and Taguchi method. Performance of the process is verified through experiments.

• 소성∙가공
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• 제20권4호
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• pp.291-295
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• 2011

The injector housing has two functions, namely, positioning the injector and protecting it from coolant. The conventional manufacturing process of the injector housing by machining has some drawbacks such as considerable loss of material and environmental pollution caused by excessive use of cutting oil. In this paper, precision cold forging is proposed as a new manufacturing process in order to improve these issues. A numerical study was conducted to compute the metal flow, strain, load and other process variables using DEFORM-2D, a finite element analysis(FEA) code for metal forming. Two process methods were investigated and optimal conditions were computed with the FEA code. A prototype was manufactured from the optimal process method and the metal flow and hardness were obtained from the prototype.

• 디지털융복합연구
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• 제13권8호
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• pp.301-313
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• 2015

현대의 기업경영에서 생산성과 효율성을 높이기 위해 제조 현장에 로봇기술의 도입은 핵심적인 기업경영사항 중에 하나이다. 이에 본 연구는 국내 중소 제조기업을 대상으로 지능형 로봇 기술 도입이 기술, 조직, 환경특성의 총 6개 변수(인지된 직접적 유익성, 인지된 간접적 유익성, 혁신성, 위험감수성, 인지된 산업압력, 인지된 정부압력)가 기업의 프로세스 혁신에 어떤 영향을 미치는지 검증하고자 하였다. 총 77개의 중소 제조기업의 자료로 Partial Least Square(PLS) 접근방법을 사용하여 연구모형의 변수간 인과관계를 분석하였다. 연구결과, 인지된 정부압력을 제외한 총 5가지 요소들이 기업 프로세스 혁신에 중요한 영향을 미치는 것으로 나타났다. 이러한 연구결과를 바탕으로 지능형 로봇을 도입하여 기업 프로세스 혁신을 위한 이론적, 실무적 시사점을 제시하였다.