• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.10
• /
• pp.296-302
• /
• 2019

In this study, a basic durability assessment was performed by selecting the main part of a trial product of a shale shaker, which is one of components for a mud circular system. For a preliminary durability assessment, it was assumed that the lifetime of the bearing for the vibrator motor and the stiffness of the support spring are affected by the vibration when the motor operates continuously. In the case of the motor, the initial p-p level was 0.72 g, but after 100 hours of operation, the p-p level was rapidly increased to 1.26 g. Bearing defects could be estimated through ball defect frequency analysis. In the case of the spring, the stiffness of the spring was reduced by approximately 3.78% at the end of 2,000 hours of the fatigue-durability test by applying excitation conditions to shale shaker body. In the future, we will analyze the influence of the particle removal efficiency of the shale shaker.

• Transactions of Materials Processing
• /
• v.30 no.6
• /
• pp.291-300
• /
• 2021

Currently, starting with electric vehicles, the application of ultra-high-strength steel sheets and light metals has expanded to improve mileage by reducing vehicle weight. At a time when internal combustion engine vehicles are rapidly changing to electric vehicles, the application of ultra-high-strength steel is expanding to satisfy both weight reductions and the performance safety of the chassis parts. There is an urgent need to improve the quality of parts without defects. It is particularly difficult to estimate the part formability through the finite element method (FEM) in the burring operation, so product design has been based on the hole expansion ratio (HER) and experience. In this study, design of experiment (DOE), analysis of variance (ANOVA), and regression analysis were combined to optimize the formability by adjusting the process variables affecting the burring formability of ultra-high-strength steel parts. The optimal variables were derived by analyzing the influence of variables and the correlation between the variables through FE analysis. Finally, the optimized process parameters were verified by comparing experiment with simulation. As for the main influence of each process variable, the initial hole diameter of the piercing process and the shape height of the preforming process had the greatest effects on burring formability, while the effect of a lower round of punching in the burring process was the least. Moreover, as the diameter of the initial hole increased, the thickness reduction rate in the burring part decreased, and the final burring height increased as the shape height during preforming increased.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.42 no.1
• /
• pp.1-7
• /
• 2019

In the modern industrial period, the introduction of mass production was most important progress in civilization. Die-casting process is one of main methods for mass production in the modern industry. The aluminum die-casting in the mold filling process is very complicated where flow momentum is the high velocity of the liquid metal. Actually, it is almost impossible in complex parts exactly to figure the mold filling performance out with the experimental knowledge. The aluminum die-castings are important processes in the automotive industry to produce the lightweight automobile bodies. Due to this condition, the simulation is going to be more critical role in the design procedure. Simulation can give the best solution of a casting system and also enhance the casting quality. The cost and time savings of the casting layout design are the most advantage of Computer Aided Engineering (CAE). Generally, the relations of casting conditions such as injection system, gate system, and cooling system should be considered when designing the casting layout. Due to the various relative matters of the above conditions, product defects such as defect extent and location are significantly difference. In this research by using the simulation software (AnyCasting), CAE simulation was conducted with three layout designs to find out the best alternative for the casting layout design of an automotive Oil Pan_BJ3E. In order to apply the simulation results into the production die-casting mold, they were analyzed and compared carefully. Internal porosities which are caused by air entrapments during the filling process were predicted and also the results of three models were compared with the modifications of the gate system and overflows. Internal porosities which are occurred during the solidification process are predicted with the solidification analysis. And also the results of the modified gate system are compared.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.17 no.5
• /
• pp.45-51
• /
• 2018

Roll forming refers to the production of long plate-molded products, such as panels, pipes, tubes, channels, and frames, by continuously causing the bending deformation to thin plates using rotating rolls. As the roll forming method has advantages in terms of mass production because of its excellent productivity, the size of the roll forming industry has been continuously increasing and the roll forming method is increasingly being used in diverse industrial fields as a very important processing method. Furthermore, as the roll forming method mainly depends on the continuous bending deformation of the plate materials, the time and the cost of the heterogeneous materials developed in the process are relatively large when considered from the viewpoint of plastic working because many processes are continuously implemented. The existing studies on roll forming manufacturing have reported the loss of large amounts of time and materials when the raw materials or product types were changed; further, they have stated that the use of this method can hardly guarantee the uniformity of the formed shapes and the consistency in terms of size and cannot detect all the defects occurring during the mass production and related to the dimensions. Therefore, in this research, a real-time process data-based smart roll forming method that can be applied to multiple products was studied. As a result, a roll forming system was implemented that remembers and automatically sets the changes in the finely adjusted values of the supplied quantities of individual heterogeneous materials so that the equipment setting changing time for heterogeneous material replacements or changes in the products being produced can be shortened. It also secures the uniformity of the products so that more competitive and precise slide-rail products can be mass-produced with improvements in the quality, price, and productivity of the products.

• Corrosion Science and Technology
• /
• v.19 no.6
• /
• pp.296-301
• /
• 2020

Failure analysis on the welded type 304 pipe used for cooling water piping in the district heating primary side was conducted. Inorganic elements and bacteria in the cooling water and in corrosion products were analyzed, and the weldment was inspected by microscopy and a sensitization test. Corrosion damages were observed in the heat-affected zone, on weld defects such as incomplete fusion or excessive penetration caused by improper welding, or/and at the 6 o'clock position along the pipe axial direction. However, the level of concentration of chloride in the cooling water as low as 80 ppm has been reported to be not enough for even a sensitized type 304 steel, meaning that the additional corrosive factor was required for these corrosion damages. The factor leading to these corrosion damages was drawn to be the metabolisms of the types of bacteria, which is proved by the detection of proton, sulfur containing species, biofilms, and both bacteria and corrosion product analyses.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.44 no.1
• /
• pp.60-70
• /
• 2021

Recently, with the development of technologies for the fourth industrial revolution, convergence and complex technology are being applied to aircraft, electronic home appliances and mobile devices, and the number of parts used is increasing. Increasing the number of parts and the application of convergence technologies such as HW (hardware) and SW (software) are increasing the No Defect Found (NDF) phenomenon in which the defect is not reproduced or the cause of the defect cannot be identified in the subsequent investigation systems after the discovery of the defect in the product. The NDF phenomenon is a major problem when dealing with complex technical systems, and its consequences may be manifested in decreased safety and dependability and increased life cycle costs. Until now, NDF-related prior studies have been mainly focused on the NDF cost estimation, the cause and impact analysis of NDF in qualitative terms. And there have been no specific methodologies or examples of a working-level perspective to reduce NDF. The purpose of this study is to present a practical methodology for reducing NDF phenomena through data mining methods using quantitative data accumulated in the enterprise. In this study, we performed a cluster analysis using market defects and design-related variables of mobile devices. And then, by analyzing the characteristics of groups with high NDF ratios, we presented improvement directions in terms of design and after service policies. This is significant in solving NDF problems from a practical perspective in the company.

• Journal of the Microelectronics and Packaging Society
• /
• v.29 no.2
• /
• pp.65-71
• /
• 2022

In the case of Mobile PKG Trend is in a situation where a decrease in Mold Top Margin is inevitable due to its miniaturization and high capacity product requirements. However, conventional laser marking technology has an average depth of deep, and when applied to narrow top margin products, PKG strength is expected to decrease due to overlapping processing, and reliability is reduced due to poor quality such as chip damage due to laser exposure. Therefore, we have secured the technology through research on low-depth laser marking solutions that can accommodate narrow top margin products. As a result of the evaluation of applicable technology application for PKG development products, it was verified that the marking depth decreased by 67% reduced and the PKG strength increased by 12%. Furthermore, the quality verification of Laser Damage that can occur through PKG Mechanical analysis was performed, and no Chip Damage defects were found. This ensured the stability of mass production application quality.

• Korean Journal of Materials Research
• /
• v.31 no.12
• /
• pp.704-709
• /
• 2021

In the flux used in the batch galvanizing process, the effect of the component ratio of NH₄Cl to ZnCl₂ on the microstructure, coating adhesion, and corrosion resistance of Zn-Mg-Al ternary alloy-coated steel is evaluated. Many defects such as cracks and bare spots are formed inside the Zn-Mg-Al coating layer during treatment with the flux composition generally used for Zn coating. Deterioration of the coating property is due to the formation of AlCl_x mixture generated by the reaction of Al element and chloride in the flux. The coatability of the Zn-Mg-Al alloy coating is improved by increasing the content of ZnCl₂ in the flux to reduce the amount of chlorine reacting with Al while maintaining the flux effect and the coating adhesion is improved as the component ratio of NH₄Cl to ZnCl₂ decreases. Zn-Mg-Al alloy-coated steel products treated with the optimized flux composition of NH₄Cl·3ZnCl₂ show superior corrosion resistance compared to Zn-coated steel products, even with a coating weight of 60 %.

• Design & Manufacturing
• /
• v.16 no.3
• /
• pp.9-15
• /
• 2022

In order to reduce the manufacturing costs of the glass lens, it is necessary to manufacture a lens using a UV curable resin or a thermosetting resin, which is a curable material, in order to replace a glass lens. In the case of forming a lens using a thermosetting material, it is necessary to form several lenses at once using the wafer-level lens manufacturing technologies due to the long curing time of the material. When a lens is manufactured using a curable material, an error in the shape of the lens due to the shrinkage of the material during the curing process is an important cause of defects. The major factors for these shape errors and deformations are the shrinkage and the change of mechanical properties in the process of changing from a liquid material during curing to a solid state after complete curing. Therefore, it is necessary to understand the curing process of the material and to examine the shrinkage rate and change of physical properties according to the degree cure. In addition, it is necessary to proceed with CAE for lens molding using these and to review problems in lens manufacturing in advance. In this study, the viscoelastic properties of the material were measured during the curing process using a rheometer. Using the results, Rheological investigation of cure kinetics was performed. At the same time, The shrinkage of the material was measured and simple mathematical models were created. And using the results, the molding process of a single lens was analyzed using Comsol, a commercial S/W. In addition, the experiment was conducted to compare and verify the CAE results. As a result, it was confirmed that the shrinkage rate of the material had a great influence on the shape precision of the final product.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.2
• /
• pp.199-206
• /
• 2022

A malfunction or breakdown of a manufacturing facility leads to product defects and the suspension of production lines, resulting in huge financial losses for manufacturers. Due to the spread of smart factory services, a large amount of data is being collected in factories, and AI-based research is being conducted to predict and diagnose manufacturing facility breakdowns or manufacturing site efficiency. However, because of the characteristics of manufacturing data, such as a severe class imbalance about abnormalities and ambiguous label information that distinguishes abnormalities, developing classification or anomaly detection models is highly difficult. In this paper, we present an deep learning algorithm for anomaly detection of a manufacturing facility using reconstruction loss of CNN-based model and ananlyze its performance. The algorithm detects anomalies by relying solely on normal data from the facility's manufacturing data in the exclusion of abnormal data.