• Journal of Korea Foundry Society
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• v.13 no.1
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• pp.62-70
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• 1993

This study presents the effect of applied pressure on the preform deformation during squeeze casting of $Al_2O_3$ short fiber reinforced aluminum alloy (AC8A) metal matrix composites. A preliminary model based on the general beam theory is suggested for the prediction of the preform deformation. Two different commercially available $Al_2O_3$ short fiber (Saffil, Kaowool) were used to study the influence of the fibers on the microstructure and mechanical properties of the squeeze cast $Al/Al_2O_3$ composites. The composites were fabricated with the applied pressure of 75 MPa which was found to be the optimum condition for the squeeze casting of the composites in this study. For the amorphous Kaowool fiber, hard crystalline Mullite phase was formed with heat treatment. Both of amorphous and the crystallized Kaowool fibers were used to fabricate $Al/Al_2O_3$ composites. Microhardness of crystallized Kaowool fiber revealed higher than that of the amorphous Kaowool fiber in the squeeze cast composites. It was also found that the wear resistance of Kaowool fiber reinforced composites increased with the amount of Mullite.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.6
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• pp.684-693
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• 2016

The luxury car industry has grown 10.5 % every year from 2010 to 2014. For this reason, it is very important for automotive companies to improve profitability and brand value. High-performance brake systems have become an absolute necessity because of the increase in engine power and customer preference among other factors. Also, competing automotive companies actively reinforce domestic production in order to maintain quality and infrastructure for luxury cars. In this regard, we demonstrated new carbon ceramic brakes to improve brake reliability for luxury cars and to improve the competitiveness of automotive companies. Finally, we propose the next-generation braking technology by predicting technological evolution trends.

• Journal of the Korean Society of Clothing and Textiles
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• v.38 no.5
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• pp.611-626
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• 2014

Reading and foreseeing fashion trends is crucial and difficult in the fashion industry due to accelerated and diversified changes in fashion trends. We use network analysis to investigate fashion trends from 2004 to 2013 in order to find the inter-relevance among fashion trends. We extracted words from fashion trend info for women's wear provided by Samsung Design Net, created a 2-mode network of seasons and trend languages, and visualized this network using NodeXl program. Fashion trends repeated a unique pattern during the period. In the first half (2004-2008), retro modern, feminine modern, and ecological modern were dominant trends in consecutive order. The years 2009-2013 witnessed distinctive fashion trends in S/S seasons and in F/W seasons. 11F/W, 12F/W and 13F/W seasons were characterized by artistic creative style. From 2010, natural style dominated S/S seasons. 10S/S and 12S/S seasons were distinguished as a calm natural style that reflected a peaceful and simple life. In 11S/S and 13S/S seasons, soft natural style emerged as a sign of increased importance of inner spirit and natural energy. A seasonal reappearance of trends was observed every two years in S/S seasons that enabled the prediction that 14S/S will see another version of natural style. A macroscopic trend for the last 10 years was represented by the keywords 'modern' and 'natural'. 'Modern' involved the past styles such as 60's, Baroque and the origin of human life. 'Natural' was connected with design elements such as material, silhouette and color. Managerial implications and future study directions are discussed based on the results.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.15-21
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• 2019

The fourth industrial revolution is noted. It is a smarter factory. At present, research on CNC (Computerized Numeric Controller) is actively underway in the manufacturing field. Domestic CNC equipment, acoustic sensors, vibration sensors, etc. This study can improve efficiency through CNC. Collect various data such as X-axis, Y-axis, Z-axis force, moving speed. Data exploration of the characteristics of the collected data. You can use your data as Random Forest (RF), Extreme Gradient Boost (XGB), and Support Vector Machine (SVM). The result of this study is CNC equipment.

• Structural Engineering and Mechanics
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• v.86 no.1
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• pp.119-137
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• 2023

The purpose of this research is to assess the performance of CBN and ceramic tools during the dry turning of gray cast iron EN GJL-350. During the turning operation, the variable machining parameters are cutting speed, feed rate, depth of cut and type of the cutting material. This contribution consists of two sections, the first one deals with the performance evaluation of four materials in terms of evolution of flank wear, surface roughness (2D and 3D) and cutting forces. The focus of the second section is on statistical analysis, followed by modeling and optimization. The experiments are conducted according to the Taguchi design L₃₂ and based on ANOVA approach to quantify the impact of input factors on the output parameters, namely, the surface roughness (Ra), the cutting force (Fz), the cutting power (Pc), specific cutting energy (Ecs). The RSM method was used to create prediction models of several technical factors (Ra, Fz, Pc, Ecs and MRR). Subsequently, the desirability function approach was used to achieve a multi-objective optimization that encompasses the output parameters simultaneously. The aim is to obtain optimal cutting regimes, following several cases of optimization often encountered in industry. The results found show that the CBN tool is the most efficient cutting material compared to the three ceramics. The optimal combination for the first case where the importance is the same for the different outputs is Vc=660 m/min, f=0.116 mm/rev, ap=0.232 mm and the material CBN. The optimization results have been verified by carrying out confirmation tests.

• Steel and Composite Structures
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• v.34 no.5
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• pp.681-698
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• 2020

The paper addresses contribution to the modeling and optimization of major machinability parameters (cutting force, surface roughness, and tool wear) in finish dry hard turning (FDHT) for machinability evaluation of hardened AISI grade die steel D₃ with PVD-TiN coated (Al₂O₃-TiCN) mixed ceramic tool insert. The turning trials are performed based on Taguchi's L₁₈ orthogonal array design of experiments for the development of regression model as well as adequate model prediction by considering tool approach angle, nose radius, cutting speed, feed rate, and depth of cut as major machining parameters. The models or correlations are developed by employing multiple regression analysis (MRA). In addition, statistical technique (response surface methodology) followed by computational approaches (genetic algorithm and particle swarm optimization) have been employed for multiple response optimization. Thereafter, the effectiveness of proposed three (RSM, GA, PSO) optimization techniques are evaluated by confirmation test and subsequently the best optimization results have been used for estimation of energy consumption which includes savings of carbon footprint towards green machining and for tool life estimation followed by cost analysis to justify the economic feasibility of PVD-TiN coated Al₂O₃+TiCN mixed ceramic tool in FDHT operation. Finally, estimation of energy savings, economic analysis, and sustainability assessment are performed by employing carbon footprint analysis, Gilbert approach, and Pugh matrix, respectively. Novelty aspects, the present work: (i) contributes to practical industrial application of finish hard turning for the shaft and die makers to select the optimum cutting conditions in a range of hardness of 45-60 HRC, (ii) demonstrates the replacement of expensive, time-consuming conventional cylindrical grinding process and proposes the alternative of costlier CBN tool by utilizing ceramic tool in hard turning processes considering technological, economical and ecological aspects, which are helpful and efficient from industrial point of view, (iii) provides environment friendliness, cleaner production for machining of hardened steels, (iv) helps to improve the desirable machinability characteristics, and (v) serves as a knowledge for the development of a common language for sustainable manufacturing in both research field and industrial practice.

• Nuclear Engineering and Technology
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• v.55 no.11
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• pp.3940-3955
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• 2023

A new method of numerical simulating prediction and decontamination effect evaluation for abrasive jet decontamination to radioactively contaminated metal is proposed. Based on the Computational Fluid Dynamics and Discrete Element Model (CFD-DEM) coupled simulation model, the motion patterns and distribution of abrasives can be predicted, and the decontamination effect can be evaluated by image processing and recognition technology. The impact of three key parameters (impact distance, inlet pressure, abrasive mass flow rate) on the decontamination effect is revealed. Moreover, here are experiments of reliability verification to decontamination effect and numerical simulation methods that has been conducted. The results show that: ⁶⁰Co and other homogeneous solid solution radioactive pollutants can be removed by abrasive jet, and the average removal rate of Co exceeds 80%. It is reliable for the proposed numerical simulation and evaluation method because of the well goodness of fit between predicted value and actual values: The predicted values and actual values of the abrasive distribution diameter are Ф57 and Ф55; the total coverage rate is 26.42% and 23.50%; the average impact velocity is 81.73 m/s and 78.00 m/s. Further analysis shows that the impact distance has a significant impact on the distribution of abrasive particles on the target surface, the coverage rate of the core area increases at first, and then decreases with the increase of the impact distance of the nozzle, which reach a maximum of 14.44% at 300 mm. It is recommended to set the impact distance around 300 mm, because at this time the core area coverage of the abrasive is the largest and the impact velocity is stable at the highest speed of 81.94 m/s. The impact of the nozzle inlet pressure on the decontamination effect mainly affects the impact kinetic energy of the abrasive and has little impact on the distribution. The greater the inlet pressure, the greater the impact kinetic energy, and the stronger the decontamination ability of the abrasive. But in return, the energy consumption is higher, too. For the decontamination of radioactively contaminated metals, it is recommended to set the inlet pressure of the nozzle at around 0.6 MPa. Because most of the Co elements can be removed under this pressure. Increasing the mass and flow of abrasives appropriately can enhance the decontamination effectiveness. The total mass of abrasives per unit decontamination area is suggested to be 50 g because the core area coverage rate of the abrasive is relatively large under this condition; and the nozzle wear extent is acceptable.