• Proceedings of the Korean Reliability Society Conference
• /
• 2011.06a
• /
• pp.257-264
• /
• 2011

In this study, we performed sensitivity study of the $217Plus^{TM}$ system model to various parameters. Specific attention was put to logistics model and its behavior has been examined in terms of non-component failure causes. We first briefly explained the $217Plus^{TM}$ methodology with system level failure rate evaluation. We then applied experimental designs with several failure causes as factors. We used an orthogonal array with three levels of each parameter. Our results indicate that cannot duplicate, induced, and wear-out causes have dominant effects on the system failures and design, parts, and system management have much less but a little strong effects. The results in this study not only figure out the behavior of the predicted failure rate as functions of failure causes but provide meaningful guidelines for practical applications.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.13 no.5
• /
• pp.50-56
• /
• 2014

A technique based on the finite element method (FEM) is used in the simulation of metal cutting process. This offers the advantages of the prediction of the cutting force, the stresses, the temperature, the tool wear, and optimization of the cutting condition, the tool shape and the residual stress of the surface. However, the accuracy and reliability of prediction depend on the flow stress of the workpiece. There are various models which describe the relationship between the flow stress and the strain. The Johnson-Cook model is a well-known material model capable of doing this. Low-alloy steel is developed for a dry storage container for used nuclear fuel. Related to this, a process analysis of the plastic machining capability is necessary. For a plastic processing analysis of machining or forging, there are five parameters that must be input into the Johnson-Cook model in this paper. These are (1) the determination of the strain-hardening modulus and the strain hardening exponent through a room-temperature tensile test, (2) the determination of the thermal softening exponent through a high-temperature tensile test, (3) the determination of the cutting forces through an orthogonal cutting test at various cutting speeds, (4) the determination of the strain-rate hardening modulus comparing the orthogonal cutting test results with FEM results. (5) Finally, to validate the Johnson-Cook material parameters, a comparison of the room-temperature tensile test result with a quasi-static simulation using LS-Dyna is necessary.

• Journal of Digital Convergence
• /
• v.19 no.11
• /
• pp.445-456
• /
• 2021

The purpose of this study is to identify the importance of variables affecting women's golf wear sales with macroeconomic variables and consumer selling prices that affect consumers' purchasing behavior, and to propose a price strategy to increase sales of golf wear. Data of domestic women's golf wear brands were analyzed using decision tree algorithms and ensemble. Consumer selling price is the most significant factors in terms of sales volume for T-shirt, pants and knit, while categories were found to be the most important factors in addition to consumer sales prices for skirt and one piece dress. These findings suggest that items have different economic variables that affect consumers' purchasing behavior, suggesting that sales and profits can be maximized through appropriate price strategies.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.3 no.1
• /
• pp.7-14
• /
• 2004

Machining error is defined the normal distance between designed surface and actual tool path with tool deflection. This is inevitably caused by the tool deflection, tool wear, thermal effect and machine tool errors and so on. Among these factors, tool deflection is usually known as the most significant factor of machining error. Tool deflection problem is analyzed using Instantaneous horizontal cutting forces. The high quality and precision of machining products are required in finishing. In order to achieve these purposes, it is necessary work that decrease the machining error. This paper presents a study on the machining error caused by the tool deflection in ball end milling of 2 dimensional surface. Tool deflection model and simple machining error prediction model are described. This model is checked the validity with machining experiments of 2 dimensional surface. These results may be used to decrease machining error and tool path decision.

• Journal of the Korean Society for Precision Engineering
• /
• v.15 no.6
• /
• pp.124-138
• /
• 1998

Particles reinforced MMCs have many advantages over monolithic metals including a higher specific modulus, higher specific strength, better properties at elevated temperatures and better wear resistance. SiC$_p$/A16061 composites have good results in its mechanical properties. This work investigates SiC$_p$/A16061 composites in the microscopic view and compares the analytical results with the experimental ones. The discrepancy of the material properties between the reinforced particle, SiC$_p$, and the matrix material, A16061 appears to be so significant. Especially the coefficient of thermal expansion(CTE) of A16061 is 5 times larger than that of SiC$_p$. Thermal residual stress in MMCs is induced at high temperatures. The shape of particle is various but the theoretical model is not able to consider the nonuniform shape. Particle distribution is not homogeneous in experimental specimen. However, it is assumed to be homogeneous in simulation model. The shapes of particles are assumed to be not only perfect global but hexahedral shapes. The types of particle distribution are two - simple cubic array(SC array) and face-centered cubic array(FCC array).

• International Journal of Reliability and Applications
• /
• v.4 no.4
• /
• pp.183-190
• /
• 2003

Rail breaks and derailments can cause a huge loss to rail players due to loss of service, revenue, property or even life. Maintenance has huge impact on reliability and safety of railroads. It is important to identify factors behind rail degradation and their risks associated with rail breaks and derailments. Development of mathematical models is essential for prediction and prevention of risks due to rail and wheel set damages, rail breaks and derailments. This paper addresses identification of hazard modes, estimation of probability of those hazards under operating, curve and environmental condition, probability of detection of potential hazards before happening and severity of those hazards for informed strategic decisions. Emphasis is put on optimal maintenance and operational decisions. Real life data is used for illustration.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1999.05a
• /
• pp.93-98
• /
• 1999

Generally, the - life of die is limited by fatigue fracture or dimensional inaccuracy originated from wear. In this paper, to predict the fatigue life of the dissimilar materials die, the stress and stxain histories of die can be predicted by the analysis of elasto-plastic finite element neth hod and the elastic analysis of die during the process analysis of workpiece. Using heat shrink fit analysis, initial stress of the k r t die is computed. Also, the stress-life curve of die material can be obtained through experiment. With the above two facts, we propose the analysis method of predicting fatigue life in die. In the proposed model, tlz analysis of elastic-plastic finite element method for material is carried out by using ABAQUS. Surface force resulted from the contacting border of the die and workpiece is tmnsformed into the nodal force of die to implement elastic analysis. Besides, the proposed analysis model of die is applied to the one material and the dissimilar materials extrusion die.

• Journal of the Korean Society for Precision Engineering
• /
• v.25 no.6
• /
• pp.159-167
• /
• 2008

Cooling lubricants are used in machining operations in order to reduce friction at the tool-chip and tool-workpiece interfaces, cool both chip and tool, and remove chip. Furthermore, they influence a strong effect on the shearing mechanisms and, consequently, on the machined surface quality and tool wear. However, several researchers state that the costs related to cutting fluids is frequently higher than those related to cutting tools. Moreover, the cooling lubricants cause an increase in both worker's health and social problems related to their use and correct disposal. Therefore, many researchers have focused on the environmentally conscious machining technologies. One of the technologies is known as MQL(Minimum Quantity Lubrication) machining. In this paper, an experimental model to obtain the optimal cutting conditions in MQL turning was suggested, and the effects of cutting conditions on surface roughness and cutting force were analyzed. For these purposes, FFD (Fractional Factorial Design) and RSM (Response Surface Methods) were used for the experiment. Cutting force and surface roughness with different cutting conditions were measured through the external cylindrical turning of Al 6061 based on the experiment plan. The measured data were analyzed by regression analysis and verification experiments with random conditions were conducted to confirm the suggested experimental model.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.4
• /
• pp.1209-1223
• /
• 2022

Blood pressure is one of the key physiological parameters for determining human health, and can prove whether human cardiovascular function is healthy or not. In general, what we call blood pressure refers to arterial blood pressure. Blood pressure fluctuates greatly and, due to the influence of various factors, even varies with each heartbeat. Therefore, achievement of continuous blood pressure measurement is particularly important for more accurate diagnosis. It is difficult to achieve long-term continuous blood pressure monitoring with traditional measurement methods due to the continuous wear of measuring instruments. On the other hand, radar technology is not easily affected by environmental factors and is capable of strong penetration. In this study, by using machine learning, tried to develop a linear blood pressure prediction model using data from a public database. The radar sensor evaluates the measured object, obtains the pulse waveform data, calculates the pulse transmission time, and obtains the blood pressure data through linear model regression analysis. Confirm its availability to facilitate follow-up research, such as integrating other sensors, collecting temperature, heartbeat, respiratory pulse and other data, and seeking medical treatment in time in case of abnormalities.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.31 no.1
• /
• pp.23-29
• /
• 2018

In knee implants, contact pressure has a significant effect on wear. In this study, finite element analysis is performed using the knee implant model developed in the previous research. The contact pressures for a total of 10 knee implant materials combinations were analyzed using the combinations actually used in research and industry. In order to calculate the contact pressure, The load was applied when the flection angle of knee was $30^{\circ}$, $45^{\circ}$ and $60^{\circ}$. The result of contact pressure revealed the smallest contact pressure in the titanium alloy-UHMWPE combination. In the case of UHMWPE, contact pressure did not change much with any material used in the femur. Compared the combination with the largest contact pressure and the smallest contact pressure, the difference was 0.77%. On the other hand, Carbon / PEEK composites showed 5.3% difference when the contact pressure was the largest and the smallest. It can be seen that when the Carbon / PEEK composite material is used as the bearing part, the material of the femoral part affects the wear. This study will contribute to the prediction of knee implant wear and minimization of wear.