• Design & Manufacturing
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• 제17권1호
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• pp.1-5
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• 2023

In multi-material injection molding, since two or more materials with different process conditions are used, it is essential to maximize process efficiency by operating the cooling or heating system to a minimum. In this study, Liquid silicone rubber (LSR) that can be cured at a low temperature suitable for the multi-material injection molding was selected and the cure behavior according to the process conditions was analyzed through differential scanning calorimetry (DSC). Dynamic measurement results of DSC with different heating rate were obtained, and through this, the total heat of reaction when the LSR was completely cured was calculated. Isothermal measurement results of DSC were derived for 60 minutes at each temperature from 80 ℃ to 110 ℃ at 10 ℃ intervals, and the final degree of cure at each temperature was calculated based on the total heat of reaction identified from the Dynamic DSC measurement results. As the result, it was found that when the temperature is lowered, the curing start time and the time required for the curing reaction increase, but at a temperature of 90 ℃ or higher, LSR can secure a degree of cure of 80% or more. However, at 80 ℃., it was found that not only had a relatively low degree of curing of about 60%, but also significantly increased the curing start time. In addition, in the case of 110 ℃, the parameters were derived from experimental result using the Kamal kinetic model.

• Design & Manufacturing
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• 제17권2호
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• pp.62-69
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• 2023

In this study, we conducted a study on the optimization of injection molding conditions to minimize deformation of plastic product. The charging management system housing of the vehicle was selected as the research subject. Melting temperature, cooling temperature, packing time, and packing pressure were selected as the main factors expected to affect the deformation of molded products. Each main factor was divided into 5 levels. Optimization of injection molding conditions to minimize deformation was performed using the Taguchi Method. We performed an analysis of variance (ANOVA) to identify significant factors affecting the deformation of plastic product. In order to select injection molding conditions that minimize deformation of plastic products, injection molding analysis was additionally performed for insignificant factors. We then compared the deformation of the molded part before and after optimization. As a result of comparing the injection analysis results of the basic conditions and the injection analysis results of the optimal conditions, it was confirmed that the amount of deformation after optimization was improved by about 10.9%.

• 소성∙가공
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• 제32권1호
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• pp.20-27
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• 2023

In this study, the deformation of materials was measured using the video and tracking API of OpenCV. Circular markers attached to the material were selected the region of interests (ROIs). The position of the marker was measured from the area center of the circular marker. The position and displacement of the center point was measured along the image frames. For the verification, tensile tests were conducted. In the tensile test, four circular markers were attached along the longitudinal and transverse directions. The strain was calculated using the distance between markers both in the longitudinal and transverse direction. As a result, the stress-strain curve obtained using machine vision is compared to the stress-strain curve obtained from the DIC results. RMSE values of the strain from the machine vision and DIC were less than 0.005. In addition, as a measurement example, a bending angle and springback measurement according to bending deformation, and a moving position measurement of a punch, a blank holder, and a die by time change were performed. Using the proposed method, the deformation and displacement of the materials were measured precisely and easily.

• 한국산업융합학회 논문집
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• 제26권5호
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• pp.757-763
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• 2023

Major industrial accidents in which workers die due to fires or explosions while working at chemical substance handling workplaces continue to occur. Among the major industrial accidents that occurred between 2005 and 2021, the accident status by work situation and equipment was analyzed. Through analysis, it was confirmed that storage, reaction, and piping facilities were the main causes of the accident, and a self-checklist for each facility was developed. Verification was conducted through the supply and use groups to evaluate the suitability of the use, duties, and items of the self-checklist. The user group showed higher satisfaction than the supplier group for all three suitability of use, job, and item. In particular, since the inspection items of the self-checklist were organized around the cause of the accident derived through the analysis of actual accident cases, the satisfaction level was high in all groups. It is expected that the self-checklist developed through this study will be useful not only for large companies but also for small and medium-sized chemical industries that lack professional manpower.

• 산업경영시스템학회지
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• 제41권4호
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• pp.248-255
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• 2018

Ensuring the quality of molds is one of the major issues in mass production. In general, securing the quality of the molds is achieved by repeating grinding and die spotting after machining the molds based on engineer's decision. However, this heuristic method is affected by the engineer's skill and working environment. Therefore, a lot of time and resources are needed in order to ensure quality. In this study, ensuring the quality of molds using grinding map which is generated using automatic measurement is proposed. An automatic measuring system based on CMM (Coordinate Measuring Machine) is developed for measuring the molds. This system generates the measurement path automatically using the 3D CAD model of products. CAD (ComputerAided-Design), CAM (Computer-Aided-Manufacturing), and CAQ (Computer-Aided-Quality) technology is integrated using DMIS (Dimensional Measuring Interface Standard) format in the automatic measuring system. After measuring the molds, a grinding map is generated using the gap between the CAD model and measured values of mold. The grinding map displays the machining tendency and the required amount of grinding with values on a 3D map. Therefore, the quality of molds can be ensured with exactness and quickness based on the grinding map. This study shows that integrating the planning, measuring, and analyzing based on computer technology can solve the problem of quality assurance of mold using the proposed method, therefore the productivity can be increased.

• Design & Manufacturing
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• 제16권4호
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• pp.24-33
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• 2022

Fiber-reinforced plastics(FRPs) have excellent specific stiffness and strength, so they are usually used as automotive parts that require high rigidity and lightweight instead of metal. However, it is difficult to predict the mechanical properties of injection molded parts due to the fiber orientation and breakage of FRPs. In this paper, the fiber orientation characteristics and mechanical properties of injection molded specimens were evaluated in order to fabricate automotive transmission side covers with FRPs and design a rib structure for improvement of their rigidity. The test molds were designed and manufactured to confirm the fiber orientation characteristics of each position of the injection molded standard plate-shaped specimens, and the tensile properties of the specimens were evaluated according to the injection molding conditions and directions of specimens. A gusset-rib structure was designed to improve the additional structural rigidity of the target products, and a proper rib structure was selected through the flexural tests of the rib-structured specimens. Based on the evaluation of fiber orientation and mechanical characteristics, the optimization analyses of gate location were performed to minimize the warpage of target products. Also, the deformation analyses against the internal pressure of target product were performed to confirm the rigidity improvement by gusset-rib structure. As a result, it could be confirmed that the deformation was reduced by 27~37% compared to the previous model, when the gusset-rib structure was applied to the joining part of the target products.

• Design & Manufacturing
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• 제17권3호
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• pp.55-60
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• 2023

The fiber-reinforced plastics and cellular injection molding process can be used to efficiently reduce the weight of battery housing components of mild hybrid electronic vehicles(MHEV) made of metal. However, the fiber orientation of fiber-reinforced plastics and the growth of foaming cells are intertwined during the injection molding process, so it is difficult to predict the mechanical properties of products in the design process. Therefore, it is necessary to evaluate the mechanical properties of the materials prior to the efficient stiffness design of the target product. In this study, a study was conducted to evaluated the mechanical properties of fiber reinforced cellular injection-molded specimens. Two types of fiber-reinforced plastics that can be used in the target product were evaluated for changes in tensile properties of cellular injection-molded specimens depending on the foaming ratio and position from the injection gate. The PP and PA66 specimens showed a decrease of tensile modulus and strength of approximately 30% and 17% depending on the foaming ratio, respectively. Also, the tensile strength decreased approximately 26% and 17% depending on the position from the injection gate, respectively. As a result, it was confirmed that the PP specimens have a significantly mechanical property degradation compared to the PA66 specimens depending on the foaming ratio and position.

• Steel and Composite Structures
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• 제34권5호
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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.

• Design & Manufacturing
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• 제17권2호
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• pp.55-61
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• 2023

With femtosecond (fs) laser pulse irradiation on metals, various types of nano- and micro-scale structures can be naturally induced at the surface through laser-matter interaction. Two notable structures are laser-induced periodic surface structures (LIPSSs) and cone/spike structures, which are known to significantly modify the optical and physical properties of metal surfaces. In this work, we irradiate fs laser pulses onto various types of metals, cold-rolled steel, pickled & oiled steel, Fe-18Cr-8Ni alloy, Zn-Mg-Al alloy coated steel, and pure Cu which can be useful for precise molding and imprinting processes, and adjust the morphological profiles of LIPSSs and cone/spike structures for clear structural coloration and a larger range of surface wettability control, respectively, by changing the fluence of laser and the speed of raster scan. The periods of LIPSSs on metals used in our experiments are nearly independent of laser fluence. Accordingly, the structural coloration of the surface with LIPSSs can be optimized with the morphological profile of LIPSSs, controlled only by the speed of the raster scan once the laser fluence is determined for each metal sample. However, different from LIPSSs, we demonstrate that the morphological profiles of the cone/spike structures, including their size, shape, and density, can be manipulated with both the laser fluence and the raster scan speed to increase a change in the contact angle. By injection molding and imprinting processes, it is expected that fs laser-induced surface structures on metals can be replicated to the plastic surfaces and potentially beneficial to control the optical and wetting properties of the surface of injection molded and imprinted products.

• Design & Manufacturing
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• 제17권4호
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• pp.1-7
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• 2023

In the fabrication of curved multi-display glass for automotive use, the surface roughness of the mold is a critical quality factor. However, the difficulty in detecting micro-cutting signals in a micro-machining environment and the absence of a standardized model for predicting micro-cutting forces make it challenging to intuitively infer the correlation between cutting variables and actual surface roughness under machining conditions. Consequently, current practices heavily rely on machining condition optimization through the utilization of cutting models and experimental research for force prediction. To overcome these limitations, this study employs a surface roughness prediction formula instead of a cutting force prediction model and converts the surface roughness prediction formula into experimental data. Additionally, to account for changes in surface roughness during machining runtime, the theory of position variables has been introduced. By leveraging artificial neural network technology, the accuracy of the surface roughness prediction formula model has improved by 98%. Through the application of artificial neural network technology, the surface roughness prediction formula model, with enhanced accuracy, is anticipated to reliably perform the derivation of optimal machining conditions and the prediction of surface roughness in various machining environments at the analytical stage.